9.2.1 A Growing Supply of Online Help, but Not Always User-Centered

Sandefur recently surveyed what digital legal help tools exist, and what forms of assistance they offer to users trying to use technology for self-help.Footnote ²⁶ Her survey found 322 digital legal tools specifically for nonlawyer users. This included legal help websites with guides and forms, legal dictionaries to clarify jargon, lawyer referral service platforms, and then tools that provide almost end-to-end support for a specific problem (including diagnosis of an issue, evidence gathering, process guides, form assembly, filing, and follow-up). Sandefur observed a mismatch between what the tools offer and the apparent justice needs desired by the public, as well as the issue areas served.Footnote ²⁷ Many of the digital legal tools were focused on providing information rather than facilitating user action. They also did not necessarily match the most common user needs reported by people: household finances, health and insurance, consumer problems, family problems, housing, and immigration. This study points to the need for more evaluation of the supply of online legal help, and the development of measures that can encourage more supply that matches the demands and preferences of people in need.

9.2.2 People Finding Inappropriate Resources on the Internet

Catrina Denvir has researched how different demographic groups, including young adults and senior citizens in the UK, attempt to use online search to deal with life and legal problems. Her research includes both simulation labs to analyze how people search for help and website assessments to measure the quality of the help people receive.Footnote ²⁸ Denvir’s work found some common patterns in people’s behavior online. Many start with a search engine, type in short questions, and try to find pages that could help them. She observed that young people tended to find and use information with little regard to the importance of jurisdiction. Even as digital natives, they often were unable to use the Internet to get correct information on their problem. In some cases, the young people got distracted by irrelevant information, trying to apply it to their situation, even if it was not legally correct to do so. These lab studies confirm that more people are trying to use the Internet to find help but raise concerns about people (including digital natives) finding “help” that in fact has incorrect, out-of-jurisdiction, or anecdotal information that may lead them astray.

9.2.3 Preferences for Clear, Authoritative, Open Access, Comprehensive Resources

My own earlier research performed lab simulations, in which US adults were asked how they might respond to a legal problem using the Internet.Footnote ²⁹ This study found that respondents, as in Denvir’s studies, preferred to start with a search engine like Google to find help for their civil justice problem. And as with Denvir’s respondents, they often ignored the importance of jurisdiction, and they sought out peer-to-peer anecdotes on forums. The study also had respondents evaluate different commercial and public interest legal help websites and express their reasons and preferences for the ideal online assistance. Most all respondents wanted a tool that met the following criteria:Footnote ³⁰

• • Authoritative, if not directly from the government, then closely affiliated with it;

• • Open Access, without paywalls, advertisements, or upselling – ideally being offered by a public interest actor rather than a commercial one;

• • Modern Design and Technical Capabilities, that offer mobile-friendly, intuitive, and interactive resources, and that are accessible to people with disabilities;

• • Comprehensive, with resources not just for initial understanding of a problem area, but also for taking action to respond to a problem.

These preferences echo Sandefur’s concerns that current digital tools are not comprehensive enough (providing only information rather than tools to take action). The user preferences also suggest categories for a standard evaluation metric, which researchers could use to measure if sites are sufficiently meeting people’s needs for usability, accessibility, and trustworthiness.

9.2.4 Open Questions for Further Research

Research studies so far on the Internet’s role in access to justice have been relatively small, with surveys, simulation tasks, and user interviews of small groups of people. What is missing is a broader examination of how people use the Internet to seek help for justice problems. The early research has laid the groundwork: More people are going online to seek help, and there are more sites, tools, and apps being built to serve them. But what do we actually know about the supply and demand of legal help online?

Public health data-driven research can provide legal researchers with models for evaluating the Internet’s use for access to a public good. The rise of digital epidemiology, infoveillance, and infodemiologyFootnote ³¹ in the public health field offers lessons for legal researchers exploring how people are seeking and finding help for justice problems, on a population level. Digital epidemiology and infoveillance involve drawing upon digital sources of data where people share information about themselves, like on search engines, social media sites, and other platforms. This data can then be analyzed through techniques like natural language processing to identify patterns, intents, and possible problems. Digital epidemiology has been used to analyze internet datasets to identify possible influenza outbreaks based on patterns of user searches, mental health risks based on online forum posts, and risk of being infected with HIV based on tweets.Footnote ³² These techniques have identified patterns of people’s medical needs, their preferences for assistance, and the coming outbreak of a crisis – though they may be problematic if relied upon as the sole evidence for where to deploy resources or make policy.Footnote ³³

Legal researchers might employ techniques akin to digital epidemiology in order to establish broader, population-level understandings of access to justice on the Internet. Returning to the core research questions introduced previously, but with a richer sense of the state of the field, new research might ask:

1. 1. What is the quantity of demand and supply for legal help on the Internet? What is the volume of assistance being sought out? Does the supply match the demand? Are there “online legal help deserts,” with minimal resources for certain issue areas? These can help make better agendas of where resources should be spent in creating more online help.

2. 2. What is the quality of the supply of legal help, and the matching of people to this help? Are the websites and tools online providing resources that people want to use, are able to use, and that get them to good outcomes? And are intermediary platforms directing people to higher-quality help, or to lower-quality help? Research around quality of supply and quality of intermediary’s matching can help set better policy about what kinds of online tools should be funded, and what internet platforms like search engines and social media ought to prioritize in their algorithms.

3. 3. Are there harms occurring when people seek help on the Internet? Are people finding malicious or unintentional misinformation about their legal options, processes, and outcomes online? This may be because of their own misunderstanding of jurisdiction, their reliance on anecdotal advice, frauds and scams, or intentional misinformation campaigns. As with public health concerns over misinformation and over harms of medical advice being given over the Internet, legal practitioners and policy makers could benefit from more research on whether and how people are finding misinformation about their justice problems online, and what harms these may cause. This could lead to more intentional strategies by service providers, policy makers, and internet platforms to address misinformation and support quality sources of assistance.

This chapter, as already noted, tackles the first of these questions, about the quantity of supply and demand for legal help online. It provides initial data sources, techniques, and findings that can offer some insight into how the Internet is functioning in people’s access to justice.

9.3.1 Intermediary Platforms Used for Justice Problem-Solving

The main intermediaries for justice problems are likely to be the same as general problem-solving intermediaries: search engines, voice assistants, and social media platforms.

Search engines are platforms in which people present words, phrases, or sentences for the intermediary to then interpret and respond with sites (or direct answers). Google Search is by far the most widely used search engine. For search engines from US desktop computers in 2021, Google received 86.64 percent of search queries, Microsoft’s Bing search engine had 6.79 percent, and Yahoo, 2.75.Footnote ³⁵ For mobile searches, the companies are in a similar order – but with Google with an even higher share. Of mobile searches in the US in 2021, Google has 93.4 percent market share, Yahoo has 2.02, Bing has 1.87, and DuckDuckGo has 2.3.Footnote ³⁶

Voice assistants, in the form of mobile phone–smart device assistant or voice-enabled speakers, are another rising type of intermediary. Voice assistants are increasingly used, in particular on one’s smartphone, car, tablet, television, or computer. Over 63 percent of Americans used a voice assistant as of 2020, and 51 percent use a voice assistant on their smartphone.Footnote ³⁷ In 2020, an estimated 128 million US residents used a voice assistant at least once a month.Footnote ³⁸ Searching the Internet is the most frequent use cases for voice assistants.Footnote ³⁹ For voice assistants specifically in home speakers, Amazon’s Alexa brand (as of 2021, relying primarily on the Bing search engine) is the leading voice-enabled speaker with 69.7 percent of US market share in 2020, with Google’s Home devices (using Google Search) at 31.7 percent, and others at 18.4 percent.Footnote ⁴⁰

Social media platforms are another key intermediary. The most popular platforms among US adults as of 2021 were YouTube (81 percent use it), Facebook (69 percent), Instagram (40 percent), Pinterest (31 percent), LinkedIn (28 percent), Snapchat (25 percent), Twitter (23 percent), WhatsApp (23 percent), TikTok (21 percent), Reddit (18 percent), and Nextdoor (13 percent).Footnote ⁴¹

We can assume that the general popularity of these search engines, voice assistants, and social media sites carries over to justice problem help-seeking. These intermediaries provide opportunities for research on internet problem solving. Just like in public health research, we can use them to observe what people are searching for, how they frame their problems, what they click on, and how they behave. That said, research using these intermediaries is difficult, because they do not make their data about users’ searches, clicks, and other behavior open to researchers.

9.3.2 Provider Websites That Offer Legal Help

Apart from these intermediaries of online legal help, there are the provider websites, which offer assistance to people seeking help on a justice problem. Within the provider group, there is another division, between commercial providers and public interest providers. Commercial providers have a for-profit business model and are giving help, information, and tools in order to either upsell the user to other services or to get advertisement or referral fees from them. Public interest providers have a nonprofit business model and are trying to get assistance to the user in order to improve their outcomes. Some may aim to generate revenue through paid services, but most public interest sites are funded through grants or government funds.

9.3.3 Commercial Legal Help Supply

I surveyed the Internet for commercial websites that offered legal assistance for civil justice problems and identified over seventy sites that have over approximately 5,000 visitors per month. Some of the most prominent general commercial legal help websites are Nolo.com, Avvo.com, Findlaw.com, Legalmatch.com, AllLaw.com, and LawShelf.com. These sites offer resources for a wide variety of legal issue areas.

There is another layer down of commercial legal help suppliers: those that focus on particular areas of legal needs. Some focus on creating legal documents for estate planning, businesses, and contracts.Footnote ⁴² Other providers aim exclusively at business formation legal needs.Footnote ⁴³ Another cluster of commercial providers focuses on family law needs, like divorce and child custody.Footnote ⁴⁴ There is another cluster around bankruptcy, debt, and credit repair problems,Footnote ⁴⁵ another around disability benefits claims and navigating resources for people with special needs,Footnote ⁴⁶ and another around personal injuries and torts.Footnote ⁴⁷

In addition to sites whose mission is exclusively around providing legal help, there are also commercial sites in other, nonlegal domains that try to attract users with justice problems. In this parallel commercial group, there are sites that offer financial literacy and other professional services, such as Nerdwallet.com, Credit.com, Creditcards.com, Consumerhelpcentral.com, Studentloanhero.com, or Angieslist.com. These sites’ resources often overlap with legal help resources, especially for life problems that have both legal and financial dimensions, like debt collection, homeownership, and landlord-tenant scenarios. The other parallel commercial group are news outlets. Sites like Usnews.com, Wusa9.com, WashingtonPost.com, and Cnbc.org offer articles that provide basic overviews of legal situations, with short articles aimed at giving general discussions of various life, legal, and financial problems.

I compiled a list of the most popular commercial legal websites, using search engine optimization (SEO) tools Ahrefs and Similarweb, which list the most popular websites for common keywords. By searching for sites that appear frequently for keywords around law, legal help, legal aid, legal answers, and related issues, I identified approximately seventy commercial legal help sites. This research focused on civil justice problems (so excluding criminal and immigration law keywords). Also excluded were commercial provider websites that appear to have fewer than 5,000 visits per month.

9.3.4 Public Interest Legal Help Websites

Apart from the commercial providers, there is a robust ecosystem of public interest legal help websites. They provide similar kinds of content as the commercial ones do articles, step-by-step guides, frequently asked questions, and form-filling tools. They also tend to have contact information for legal aid attorneys, free chat with law librarians, and other on-ramps to free services.

Unlike the commercial provider sites, public interest legal help websites are almost all at the state or local region level. It is notable that there is not a single national legal aid or public interest legal help portal that gives national guidance on civil justice problems. Rather, it has been state or local actors that have created legal help portals for their region, giving guides and contacts for people looking to address their justice problems.Footnote ⁴⁸

There are some national public interest websites around specific issue areas or demographic groups. For example, there are national public interest sites for sexual assault and domestic violence,Footnote ⁴⁹ women’s law issues,Footnote ⁵⁰ landlord-tenant issues,Footnote ⁵¹ immigration issues,Footnote ⁵² and bankruptcy and debt issues.Footnote ⁵³ There are also some national legal help websites that provide specific tools or resources, like a legal dictionaries and reference materials.Footnote ⁵⁴

I identified approximately 340 civil help websites that provided free information and tools to people in the fifty states, as well as DC and Puerto Rico. I did not include local bar associations, law library, or county court websites, because the majority of them do not have substantial self-help material (though this may change in the future, and these sites might be added into future research).

Most public interest legal websites operate at the state or regional level. Within each state, frequently there is a local ecosystem of four kinds of public interest legal help websites:

1. 1. A statewide legal help portal, which provides an overview of civil justice guides, contacts, FAQs, and tools.

2. 2. A legal aid organizational website (or sites), which provides contact information, hotline numbers, clinic details, and a limited number of articles or guides on legal issues. (Some states have many regional legal aid groups, each with its own website, while others have a single main legal aid group serving the entire state.)

3. 3. A court self-help website, which offers court-focused guides, tools, forms, and service hours to self-represented litigants who have an issue in civil, family, or traffic court. (Some local county courts may have their own self-help, but typically this is run by the statewide judicial council or administrative office of the courts.)

4. 4. A free online brief advice clinic for low-income people, run through the ABA Free Legal Answers project. Not every state has a Free Legal Answers clinic, but more than thirty do.Footnote ⁵⁵

Some states, like California, Florida, and New Jersey, have many legal aid organizations and so have a large number of public interest websites. Other states, like Wyoming, North Dakota, Georgia, Wisconsin, or New Hampshire, do not have statewide legal help portals and may only have one or two public interest legal help sites.

9.4.1 Estimates of Demand from Legal Needs Surveys

One way to estimate how many people might be coming online to find help is to look at estimations of how many people experience justice problems in the US. Legal needs surveys ask adults about how often they have experienced justice problems, like situations of wage theft, eviction, debt collection, bankruptcy, domestic violence, foreclosure, access to medical treatment, and the care and custody of children and dependent adults.Footnote ⁵⁶ Sandefur’s study of a representative sample of US adults in 2013 found that two-thirds of them experienced at least one civil justice problem in the past eighteen months, with the average number of justice problems being 2.1 problems in eighteen months. Of the two-thirds of adults who reported having a problem, they averaged 3.3 needs in eighteen months.Footnote ⁵⁷

These rates of justice problems allow us to estimate how much demand there might be for legal help. By using this estimated rate of each adult experiencing 2.1 problems in eighteen months, we can use states’ adult populations to estimate how many people are experiencing justice problems in a month. This estimation is likely to overestimate the number of people coming to the Internet to seek help for a justice problem. Surveys have found that 16 percent of US adults take no action (including reaching out for assistance or searching for help) when they experience a justice problem.Footnote ⁵⁸ Accordingly, we can assume that a significant proportion of adults with a justice problem, akin to this 16 percent figure, may not come online to find help. There are not yet surveys that document the rate at which people experiencing a justice problem go onto the Internet to seek help.

I calculated each state’s expected number of justice problems per month, and the expected number of problems for which people seek help.Footnote ⁵⁹ For example, we might assume that each month in California there are around 3,572,000 justice problems, and that people might take action on approximately 3 million of them. Or in Alabama, there may be around 445,000 problems per month, and people will seek help for around 374,000 problems. In total, we can assume that the whole US population has around 25 million acted-upon justice problems per month (with acted-upon meaning that the adult takes action to try to address it). These estimates provide a rough expectation of how many adults might be seeking help online.

Using these estimates of acted-upon justice problems per state, we can approximate if supply is matching demand. Are people in a state visiting legal aid, court, and public interest websites at the rate we may expect them to? Are there 3 million visits to California legal help websites each month – or is the number substantially higher or lower? How well is the supply of public interest websites matching the demand for legal help?

9.4.2 Tracking Demand through Analytics and SEO Traffic Estimators

Aside from estimates based on surveys, another strategy to measure demand is to count the visitors to legal help websites. There is a clear gap in this strategy: Not all people searching for help with a justice problem online will in fact find their way to a legal help website. Website visit counts will not capture demand from people who might have framed their online queries in terms that may have led them to other sites – or who looked at search results and decided not to click anything. Still, the visitor counts can help us see if the expected demand matches the actual demand, and if that matches the number of people using public interest sites.

Site analytics. Sites that have an analytics tool installed can track the numbers of people who come to visit, what search terms or other sites have referred them to this site, and what pages on the site they visit. These analytics numbers are useful because they are closest to being exact counts of visitors. They are not completely accurate. Often they will undercount visitors, because of the use of ad blockers, cookie blockers, and JavaScript disablers by visitors. When a person has these blockers in place on their browser, they can prevent Google Analytics from tracking their behavior – and thus stop the site from registering their visit. Researchers can use Analytics, from websites’ administrators that have given them access or reports to their sites. These numbers will likely underestimate actual visits.

SEO platforms have developed tools to estimate the traffic to websites, even without access to websites’ administrative backends. These SEO research platforms do not offer exact numbers of how many visitors come to a specific website in a month. But they provide useful estimations of how many visitors are coming from search engines to a site.Footnote ⁶⁰

SEO traffic estimator by search keywords. One type of SEO traffic estimation tool, like that from provider Ahrefs, makes these estimates by tracking billions of keywords that people tend to search for, and then seeing how many people are searching for them each month, which sites appear for them, and which sites people click on.Footnote ⁶¹ This permits estimates of the average monthly visitors coming from search engines to a given site. The SEO traffic estimation tools will most often underestimate actual visitors to a website because of several inbuilt constraints. First, some SEO tools (like Ahrefs) track only visitors who are coming from search engines, and not from other pathways (like those directly typing in the website URL or coming from another non-search website). Second, they do not track every single keyword (or search query) that a person might type into a search engine. Though a tool like Ahrefs Traffic Estimator follows over 6.1 billion keywords, visitors might use “long-tail” searches (like, “show me a legal aid group that can help me with an eviction notice please Google”) that it does not track.

SEO traffic estimator by behavior tracking. Another SEO estimation tool, Similarweb, takes a different approach. It gathers data about users’ online activities from internet service providers, a panel of monitored devices, and shared web analytics accounts.Footnote ⁶² They use their behavioral tracking data, analytics access, and other public data sources to estimate how many people are visiting a given website. Other SEO tools have found Similarweb to provide the most accurate estimates of total visitors to a site, though they tend to overestimate visitors.Footnote ⁶³

To assess which estimation tool might be useful, I used a website that I maintain with my team at Stanford Legal Design Lab. In May 2020, our team launched a national non-profit website for housing law information, Legal Help FAQ. We have Google Analytics tracking visitors to the website and keeping counts of users and visits. According to Google Analytics, in the month of January 2021, the site had 13,520 users and 30,623 page views. Similarweb estimated that the site had 18,126 users and 31,877 visits. They overestimated visitors by 34 percent (4,606 users), and visits by 4 percent (1,254 visits). Ahref estimated total traffic from Google Search to LegalHelpFAQ to be 42 visitors in January 2021. Google Analytics indicated that we had 4,385 visitors from Google Search in January 2021. This was a substantial underestimation of search traffic to our site, with a difference of 4,343 visitors. I then proceeded to measure Similarweb’s estimates against other sites, whose administrators shared their Google Analytics reports with me (see Table 9.1).

Google Analytics tends to underestimate the number of visitors, though it is not clear by how much. Similarweb seems to overestimate the number of users visiting the site, differing from the Analytics by as much as 34 percent. Similarweb’s numbers are substantially closer to the Analytics’ numbers than the Ahrefs tool.

With those caveats on the tools’ limitations to produce exact numbers, Similarweb does provide us with rough estimates of most legal help websites’ traffic. Its ballpark estimates should not be relied upon for exact measures, but they can be approximate counts to help service providers and policy makers compare how different kinds of sites are performing and how they change over time.

9.4.3 Legal Help Site Visits as Proxy for Demand

By looking at rough estimates of visits to various types of legal help websites, we can see what kinds of justice problem-solving behavior is happening online. These numbers are estimates from Similarweb, so they may overestimate actual visitors. They are also for a single month, January 2021, which occurred during the COVID-19 pandemic, and so may be different than a typical month (without a public health emergency) (see Table 9.2).

These monthly estimates of visits to commercial legal help websites indicate that tens of millions of people come online to seek assistance and information about the law each month. Compared to our earlier estimate from legal need surveys that the US adult population has approximately 25 million justice problems per month, the visits to commercial websites almost double this estimate. This high number of visits may include “multiple visit” scenarios, in which a person with a single justice problem visits more than one website in order to find assistance. These website visits may also include visits from people outside the US, who found the resource online. Some visits may also come from legal professionals or researchers, using these websites in their own work. We cannot take each visit to a website as indication of a unique justice problem; these numbers of website visits are not direct proxies for legal need counts.

These caveats aside, this estimated traffic of over 50 million visits to US commercial legal help sites in one month strongly suggests that there is a substantial demand for legal information and assistance online. This survey also shows that there are active ecosystems of websites supplying assistance for certain legal issue areas, including immigration, public benefits and disabilities, family law, small business, bankruptcy, and personal injury.

9.4.4 Visits to Public Interest Legal Help Websites

As mentioned earlier, most public interest sites are local rather than national. There are approximately twenty public interest national sites, most of which focus on particular legal issues or provide national coverage with legal dictionaries or sets of forms.Footnote ⁶⁴ The total estimated number of visitors in January 2021 to only the national public interest websites was around 6,290,000 visitors.

This 6.2 million visitor count must be adjusted downward, though 4.49 million of those visitors were to Cornell’s Legal Information Institute (LII), which provides a legal dictionary and open access to legislation and other laws. Many users of LII are legal professionals and students using its legal reference resources. It’s impossible to discern how many of LII’s 4.49 million visitors are legal professionals versus people seeking help on their justice problem. The monthly number of laypersons seeking help on the national public interest legal sites likely lies between 1.79 and 6.29 million (see Table 9.3).

The estimated traffic to national public interest sites is substantially lower than that to national commercial help sites, by at least 44 million visits per month. The coverage of issues is also quite different. National public interest websites focus more on debt, domestic violence, and women’s law issues, and less so on family law, small business, immigration, public benefits, or housing. In some cases, such as family, benefits, and housing, the shortfall is likely because regional public interest sites are expected to serve this need. But the lack of a national public interest hub for these issues is noticeable, particularly given apparent high demand for these issues.

How do local public interest legal help websites (for instance, those of a local legal aid group or court self-help center) fare, in terms of estimated monthly traffic? Unfortunately, it is difficult to measure most courts’ self-help sites, because of the nature of their websites. Most court help pages are located as a subpage of the main court website (like https://www.azcourts.gov/selfservicecenter or https://mdcourts.gov/legalhelp). This prevents estimation of their traffic, because the Similarweb estimation tool works on only the main domain and not the subpages. I was also unable to estimate many legal aid sites’ visitors, because they apparently have fewer than 5,000 visits per month, and the Similarweb estimation tool could not reliably predict their visit count.

These limits result in a restricted measure of local public interest site visits. I ran visitor estimations for each state’s statewide legal help portal. Not every state has a dedicated “Law Help” portal. In some cases, such as Delaware or Wisconsin, it is a legal aid group’s site that functions as a de facto statewide resource. But most of the states do have something akin to Alaska Law Help, Law Help Hawaii, or Massachusetts Legal Help. The estimated visitor counts to these statewide law-help portals is a first attempt to measure people’s visits to local public interest sites.

The total estimated visitors to the statewide legal help portals were approximately 3,454,000 per month. Nine of the portals had over 100,000 estimated visitors per month, mostly from high-population states like Texas, Massachusetts, and Illinois. But the numbers of visitors did not necessarily correspond to population numbers or projected levels of justice problems (see Table 9.4).

9.5.1 State Portals as an Underdeveloped Resource

For those states whose portals get relatively few visits, this may be because there is another public interest site in their jurisdiction that has a high-traffic site. For example, in California the statewide legal help portal gets far fewer visitors than the court’s statewide Self-Help center website. In this state (unlike most others), the state court is the leader in online legal help.

Still, the estimates of monthly visitors to public interest legal help websites show that there is a broad section of the public that is not finding these free, non-profit resources when they are searching for their justice problems online. The estimated visitors to commercial websites indicate that there are tens of millions of people seeking information on legal topics on the Internet each month. A handful of public interest websites have been able to attract relatively high proportions of their potential audience. But most state portals seem to be getting visits from fewer than 20 percent of people in their state experiencing justice problems.

These findings indicate a gap that policy makers and service providers must prioritize. The supply of public interest legal help sites might be improved with more content, improved technical and design updates, and outreach strategies. The sites may be able to reach more of the people seeking legal help online if they improve their performance so that more people can find them, and more internet intermediaries are likely to place them high on search results.

How does a site improve its offerings and placement by intermediaries? One answer is investment in better content that matches what people are searching for and websites that engage visitors so that they do not click away quickly. It also involves improving the technical and design performance of the sites, so that search engines favor them. More work needs to be done with public interest sites to master these SEO techniques and content development work that many of the commercial sites have done, in order to engage the millions of people coming onto the Internet in search of help.

9.5.2 Technology Companies’ Role in Directing People to Commercial or Public Interest Sites

Another area of policy concern is the dominance of commercial legal help websites in visitor patterns over public interest websites. To be sure, commercial legal help websites are not inherently bad. For-profit entities have high-powered incentives to offer user-friendly designs, responsive technology, and content and services that match the needs of the public. Their business models, however, tend to steer people away from free legal assistance and give only basic beginning information about a legal issue rather than a full protocol of steps and process.

A standard approach is to offer short descriptive articles about a problem like eviction or debt collection, rather than a full step-by-step guide like those that might be found at public interest websites.Footnote ⁶⁶ One type of commercial model relies on attracting people to click on the site, in order to show them advertisements. These sites present short, generic articles framed around FAQs like “How Do I Stop an Eviction?” which give people descriptions about the law and options of what they can do while showing multiple advertisements for nonlegal content. These generic articles do not provide information about jurisdiction, defenses, laws, or free services a person can use.Footnote ⁶⁷ Another for-profit model provides short summaries of substantial, local legal information for free, but then with a paywall around actionable help. For example, on Nolo’s website about non-payment of rent and eviction, the site provides a summary of local legal requirements and defenses. If a visitor wants to understand how to make use of these laws, the site advertises that they should buy the website’s books, forms, and templates, or that they should hire a lawyer affiliated with the site.Footnote ⁶⁸ By contrast, public interest sites tend to give visitors a menu of free assistance, including do-it-yourself guides, form-filling tools, free legal navigators, legal aid representation, and holistic social services assistance.

Commercial websites may be getting so much traffic vis-à-vis public interest ones because they have deployed more search engine optimization strategies: producing more content that matches people’s search keywords, creating sites that people stay on for longer amounts of times, having technically capable websites, and taking other actions that make it more likely for Google and other search engines to place them higher on search results pages. Public interest organizations may, as mentioned before, improve the content and technical performance of their sites to be more competitive.

Still another factor that shapes comparative use rates is the search engine companies’ policies themselves. As with other sectors, the search engine companies could alter their ranking algorithm to prioritize court, legal aid, and other public interest legal help providers above commercial providers. Google, for example, has altered how it responds to its users’ searches around health problems or voting and elections to provide information that is sourced from vetted public interest actors rather than commercial websites. In 2015, Google partnered with the Mayo Clinic and medical doctors hired by their company to curate medical knowledge panels to show in response to people’s health searches.Footnote ⁶⁹ In 2016, Google worked with a university and foundation-supported Voting Information Project to present knowledge panels on where to vote, requirements to vote, and who is on the ballot in local elections.Footnote ⁷⁰ Could such an initiative be possible for users’ queries around evictions, foreclosures, wage theft, divorce, custody, debt collections, and domestic violence protection? Technology companies play a substantial intermediary role, directing people to resources that can answer their questions and conferring authority to those that place high in their search results. Public interest organizations may partner with these search engine intermediaries to create knowledge panels and search rank algorithms that convey key local legal help information to people searching online that would appear before the normal search results from a mix of commercial and public interest providers.

More thinking remains to be done on how best to harness the capacities, resources, and profit-seeking motivation of the commercial sector alongside the public-interest orientation and ethical approach of non-profit and legal aid groups, whether public or private. The empirical analysis presented above aims to spur some of that thinking.

10.2.1 First-Order Digital Divide(s): Access to Technology and Stable Internet Connection

Many unrepresented persons – indeed, those facing the most economic precarity – do not have reliable access to the Internet or the videoconferencing technologies to fully participate in virtual hearings. According to the Pew Research Center, many low-income Americans rely on their cellphones to access the Internet and are “smartphone-dependent” internet users, meaning that they access the Internet on their cellphones and do not have broadband internet at home. About one-in-three do not have a cell phone at all. Moreover, there are substantial disparities in access to internet broadband and computers at home,Footnote ²² with Black, Hispanic,Footnote ²³ and ruralFootnote ²⁴ households residing on the “have-not” side of the digital divide.

Troublingly, bridging these first-order digital divides by providing initial access may not be enough to ensure true, reliable, material access or meaningful participation. Material access is a multidimensional construct,Footnote ²⁵ and the ongoing struggle to ensure material access may be better understood through a lens of technology maintenance.Footnote ²⁶ Technology maintenance refers to the burdens of time, energy, and money required to maintain digital access even after ownership of a cell phone.Footnote ²⁷ Technology maintenance practices that limit functionality include: counting cell phone minutes to avoid “going over”; switching between cell phones depending on minutes; or “beeping” (calling and hanging up) to communicate without minutes.Footnote ²⁸ Moreover, users share cell phones with family members, which requires maintenance of personal relationships.Footnote ²⁹

While most low-income Americans have intermittent access to the Internet, this access is often unstable and characterized by frequent periods of disconnection and cycles of reliable unreliability.Footnote ³⁰ Low-income Americans contend with temporarily disconnected service, broken hardware, and barriers on public access. These disruptions diminish access to unemployment, healthcare, education, and social support.Footnote ³¹

10.2.2 Second-Order Digital Divide(s): Inequalities in Technological Capabilities and Efficacy

The persistence of a second-level digital divideFootnote ³² refers to the fact that differences in digital proficiencies produce inequality, often revealed by limited digital literacy or efficacy in navigating the web.Footnote ³³ Barriers to first-order access and the frictions of technological maintenance compound to produce negative attitudes toward, and perceived lack of utility of, the Internet.Footnote ³⁴ Relatedly, low-income Americans who lack a computer at home experience higher emotional costs than others when using computing technology. That is, barriers on home computers engender psychological friction toward computing technology.Footnote ³⁵ Undoubtedly, first-order structural inequalities contribute to a vicious cycle: Structural inequalities produce second-order digital divides by reducing technological efficacy, creating psychological friction, and affecting the type and quality of online activity,Footnote ³⁶ ultimately conditioning the benefits of being online.

10.3.1 Study Overview

Method. A team of six law student observers at the Indiana University Maurer School of Law and Stanford Law School engaged in structured observations of over 500 live-streamed virtual proceedings among twenty Indiana judges who handle high volumes of small claims cases (e.g., evictions, debt collection, small claims) online. These observations were conducted between March 1 and April 23, 2021 (a seven-week window). These observers accessed the virtual hearings via the Indiana Office of Court Service’s live-streaming website. To ensure that these observations focused on small claims, debt-collection, and eviction cases, these observers accessed the courts’ public daily hearing calendars and private weekly hearing calendars provided by the Indiana Office of Court Services. A detailed coding scheme was developed, and these law students were trained over the course of two weeks on how to implement this coding scheme. The observation data was inputted via a Qualtrics survey.

Measures. For purposes of this chapter, which reports preliminary results, we report three coded measures: (1) Represented by an attorney? (2) Dialed in by phone to virtual hearing (e.g., Phone number on Zoom tile or only voice heard)? and (3) Camera on? The observers coded these features of each of the over 500 live-streamed hearings, indicating in categorical terms whether these features occurred: yes, no, unsure, NA.

Data preparation. Data was entered in Qualtrics, and analyses were performed in R version 4.0.2. The full dataset of live, virtual proceeding observations included n = 503 observations, and included hearings without a subject matter indicator. These miscellaneous hearings were removed from the dataset, and the dataset was narrowed to n = 455, which included observations of small claims cases, debt-collection cases, and evictions. Next, n =106 of these 455 cases were observed by multiple law students. Accordingly, we developed an inter-rater coding analysis strategy in which data in the above-mentioned measures were retained for purposes of analysis when a majority of these multiple observers agreed when resting whether (1) a party was represented or not at the virtual hearing, (2) a party dialed into the hearing on their phone or not, or (3) a party’s camera was on or not. In the vast majority of instances, coders agreed about these aspects of a party’s appearance at the hearing. After removing the duplicate observations from the dataset, n = 349 unique observations remained. Regarding the subject matter of these cases, these n = 349 cases entailed eviction cases (n = 150), debt-collection cases (n = 103), small claims cases (n = 90), and other cases (n = 6) appearing on these high-volume dockets.

10.3.2 Preliminary Results

Representational asymmetries. We first analyzed representational asymmetries (n = 349), and in doing so, we categorized parties as represented if a lawyer appeared in their case and classified cases in which defendants/respondents defaulted as cases in which they did not have counsel. As anticipated and consistent with the literature (Figure 10.1), a majority of hearings involved representation asymmetries in which plaintiffs/claimants were represented and defendants/respondents were not (n = 209, 59.9 percent). Defendants/respondents were rarely represented (n = 5, 1.4 percent). Both parties were unrepresented in nearly 40 percent of cases (n = 135, 38.7 percent).

Figure 10.1 Virtual proceedings represented status

Technological asymmetries. We first analyzed technological symmetries in a manner that included defaults by defendant/respondents and no-shows by plaintiffs/claimants (n = 338). As revealed in Figure 10.2, the most notable observation when including defaults and no-shows is that, despite the apparent conveniences provided by remote proceedings, defendants/respondents nevertheless default in approximately 55 percent of cases (n = 186, 55.0 percent), whereas plaintiffs/claimants rarely no-show (n = 6, 1.8 percent).

Figure 10.2 Virtual proceedings matrix of tech asymmetries (including defaults)

While this apparently reflects a decrease in the default rate, the conveniences provided by remote hearings are not a panacea for addressing the challenge of defaults in these cases. Over half of defendants/respondents still default in these cases; as such, the conveniences of remote proceedings may need to be coupled with other interventions that discern and more effectively address the underlying reasons why many defendants do not to attend court hearings.

Turning now to Figure 10.3, which describes virtual proceedings where both plaintiffs/claimants and defendants/respondents actually attend (i.e., excluding defaults) (n = 149), we found that a majority of these hearings involved scenarios in which defendants/respondents dialed into these Zoom/Webex hearings on their cell phones (n = 96, 64.4 percent). Many of these instances involved technological asymmetries in which the plaintiff had full Zoom virtual capabilities and the defendant/respondent dialed into the hearing (n = 56, 37.6 percent). Rarely did the technological asymmetry favor the defendant/respondent (n = 14, 9.4 percent). In many instances, the parties both dialed into these hearings, despite the possibility of appearing virtually on Zoom (n = 40, 26.8 percent). Both parties appeared virtually in a minority of cases (n = 36, 24.2 percent). Finally, we also revealed instances in which a party appeared via Zoom with their camera off, which is distinct from dialing in per se. In these scenarios, for example, a person would be able to see others on Zoom, but their camera would be turned off and they would not be able to be seen. This occurred in an extremely small fraction of cases (n = 3, 2.0 percent). In these cases, the defendant/respondent had turned their camera off, whereas the plaintiff/claimant had their camera on, another technological asymmetry.

Figure 10.3 Virtual proceedings matrix of tech asymmetries (excluding defaults)

Representational asymmetries × technological asymmetries. We then focused specifically on cases in which lawyers appeared for the plaintiff and unrepresented defendants appeared in these remote hearings (n = 96). This analysis (Figure 10.4) reveals ways in which representational asymmetries compound with technological asymmetries. In other words, the technological asymmetries are even more pronounced when plaintiffs with lawyers face unrepresented defendants.

Figure 10.4 Virtual proceedings matrix of tech asymmetries lawyers versus unrepresented/SRL defendants

As reflected in Figure 10.4, we found that a majority of these hearings involved scenarios in which unrepresented defendants/respondents dialed into these Zoom/Webex hearings on their cell phones (n = 68, 70.8 percent). Nearly half of these cases involved technological asymmetries in which plaintiff lawyers had full Zoom virtual capabilities while unrepresented defendants/respondents dialed into the hearing (n = 45, 46.9 percent). Rarely did the technological asymmetry favor unrepresented defendants/respondents (n = 6, 6.2 percent). In many instances, both a lawyer and an unrepresented defendant dialed into these hearings (n = 23, 24.0 percent). Both parties appeared virtually in a minority of cases (n = 20, 20.8 percent).

Again, we also revealed instances in which either the lawyer or unrepresented defendant appeared via Zoom with their camera off, which is distinct from dialing in. Although this rarely occurred (n = 2, 2.1 percent) and, when it did, it was the unrepresented defendant/respondent whose camera was off, and the plaintiff lawyer whose camera was on, compounding the technological asymmetries.

10.3.3 Discussion

In summary, we found that a majority of low-income defendants/respondents in these virtual hearings are unrepresented and most are dialing into virtual court (e.g., Zoom/Webex hearings) on their cell phones. These cases involve representational asymmetries, in which repeat-player plaintiff lawyers litigate against low-income defendants who are unrepresented. Troublingly, these cases also involve technological asymmetries, in which repeat-player plaintiff lawyers regularly employ the full range of virtual interaction and videoconferencing capabilities of Zoom/Webex, while low-income unrepresented defendants whom they sue are often limited to the audio-only capabilities of their cell phones.

10.4.1 Overview: Social Production of Unrepresented Persons

The civil justice system presents courts, lawyers, and unrepresented persons with a set of situational affordances and barriers.Footnote ⁴¹ In this section, we will examine the ways in which virtual courts asymmetrically allocate situational affordances and barriers, and technological features and constraints, to lawyers and unrepresented persons. For example, lawyers can engage in fully virtual interactions, where they are able to hyper-personalize and can also Zoom in from staged law offices with reliable high-speed internet connections. Lawyers can also gaze directly into the camera – simulating eye contact with the court – while also using and perceiving nonverbal behavior to persuade. In contrast, low-income unrepresented persons who dial into Zoom court on their cell phones can only speak and hear from a distance, are often depersonalized into a black tile on the screen, cannot use or perceive nonverbal behavior, and are unable to use or perceive documents in Zoom hearings. These conditions and constraints are highly skewed and appear to exacerbate asymmetries between lawyers and unrepresented persons in virtual courts.

10.4.2 Lawyers

Situational affordances and technological features. Virtual courts provide lawyers a variety of situational affordances and technological features that may enhance their efficiency and effectiveness.

Virtual courts reduce the time and cost borne by lawyers who would otherwise have to travel to court and wait in courtrooms to attend in-person proceedings.Footnote ⁴² As a result, lawyers can reallocate this time to prepare for other cases and multitask while waiting for their virtual hearings to be called, which we observed. Moreover, lawyers often have stable, reliable internet access in their law offices and homes, and these home and law offices often contain legal resources, equipment, and staff – for instance, case files on computers, phones, fax machines, scanners, access to online legal databases, and administrative support – not available to lawyers physically present in courtrooms. We observed an instance, for example, in which a judge asked a lawyer for information specific to a case, which the lawyer did not have in hand but was able to obtain after a brief pause from a colleague in an adjacent room during the hearing.

Second, research has revealed that the inclusion of gaze awareness and upper-body nonverbal cues in a video frame may engender empathy.Footnote ⁴³ High-quality videoconferencing systems that preserve gaze and upper-body cues have been found to be as effective as face-to-face meetings in preserving empathic concern. However, when systems do not preserve these cues, empathy and rapport are degraded.Footnote ⁴⁴ The challenge, again, is the asymmetry: lawyers are more likely to have this high-quality videoconferencing technology than low-income unrepresented persons who dial into these hearings.

Finally, Zoom virtual hearings allow lawyers and others with the most technological capital, capabilities, and expertise to enhance their self-presentation above and beyond what may have been possible in an in-person hearing. This phenomenon is referred to as hyper-personalization.Footnote ⁴⁵ Lawyers can carefully curate their online impression in Zoom hearings, using filters to soften and touch up their images, placing their names on Zoom tiles, and by staging their background (whether actual or virtual).

Barriers and constraints. As many lawyers have stable, reliable high-speed internet access and the technologies necessary to participate in Zoom proceedings effectively from their home or law offices, the shift from in-person to Zoom hearings appears to impose few situational barriers. Furthermore, lawyers who Zoom into virtual hearings face few technological constraints as compared to low-income unrepresented persons who dial into Zoom hearings. These lawyers will often have access to videoconferencing equipment that preserves their gaze awareness and nonverbal behavior and have the ability to hyper-personalize their self-presentation.

10.4.3 Unrepresented Persons

Situational affordances and technological features. Like lawyers, unrepresented persons may gain conveniences, including reduced travel and child-care burdens.Footnote ⁴⁶ They may also enjoy the comfort of attending Zoom hearings from home or work (rather than attending court in person). Indeed, the Self-Represented Litigation Network has noted that virtual court proceedings may reduce the time and expenses associated with traveling, transportation, childcare, and other day-to-day costs that litigants incur when going to court.Footnote ⁴⁷

Relatedly, we observed instances where at least some unrepresented persons who attended these virtual hearings behaved quite confidently, perhaps more confidently than would be the case within an in-person hearing. This may be because, for some unrepresented persons, the convenience and lack of formality may decrease the sense of intimidation that may be present in an in-person hearing, an avenue for future research.

These conveniences may be translating to higher appearance rates, as suggested by the National Center for State Courts.Footnote ⁴⁸ Yet caution is warranted before celebrating these court statistics.

For example, when a low-income person dials into a Zoom courtroom on a cell phone, this audio-only entry is counted as an “appearance.” However, these low-income persons can neither see nor be seen by other court participants, unlike the lawyers who Zoom into these virtual courts. They are unable to perceive the facial expressions and nonverbal behaviors of other courtroom actors or to review documents used by lawyers and judges in these virtual hearings. In short, not all “appearances” are appearances in the conventional sense of what it means for something to appear to someone as an object of sight perception. In the future, we should consider the utility of moving beyond a strict dichotomy of whether a party “appeared” or not, and consider a construct that considers a continuum of the qualities of what it means for a person to appear in court. Certainly, this continuum will lend itself to many important questions that go beyond mere access, centering on equity and the experience of attending court whether online or in person.

Barriers and constraints. Unlike lawyers, the shift from in-person to Zoom hearings imposes notable situational barriers and technological constraints on low-income persons.

First, unrepresented persons must prepare exhibits and documents in advance of hearings. While these documents are filed before Zoom proceedings, courts use these documents within the proceedings themselves. When low-income persons dial into Zoom proceedings, they are unable to see the court or documents shared by or with the court during the hearing. We observed that this led to miscommunication about documents (and negative outcomes) during Zoom hearings.

Second, the shift to Zoom removes situational affordances available to low-income people who attend court in person: mainly, access to in-court self-help ecosystems. This shift may impair the ability of navigators, self-help professionals, and legal-aid providers to help unrepresented persons. Relatedly, in immigration and criminal proceedings, lawyers have experienced difficulty meeting and privately conferring with their clients before virtual hearings.Footnote ⁴⁹ Moreover, when low-income persons dial in to Zoom proceedings, they lose the ability to observe others and learn how the full complexity of the courtroom unfolds. While this may be of little value to lawyers, unrepresented persons often learn by watching. Without this opportunity to learn by watching, many unrepresented persons may not understand the process or the expectations of the court, which may decrease the effectiveness of their self-representation.Footnote ⁵⁰

Third, most low-income unrepresented persons access the Internet via cell phones that are, themselves, reliably unreliable.Footnote ⁵¹ Relatedly, many low-income Americans who have cell phones are on pay-as-you-go data plans and cannot afford to pay for the data required to attend. When these low-income Americans dial in to these hearings, they are depersonalized into black Zoom tiles in the hearing, set against a black Zoom backdrop, often with a case number (or phone number) attached to the Zoom tile. Many other low-income persons do not appear on the screen at all; rather, these Zoom tiles are hidden from the screen, and judges and lawyers merely hear their voice. For these persons, aside from this auditory presence, there is no sign that these unrepresented persons appeared at hearings at all.

10.5.1 Judge’s Perspective

From the judge’s perspective, judges can only see and be seen by the lawyer. From the judge’s vantage point, low-income unrepresented persons who dial into Zoom hearings appear as a black Zoom tile with a case ID or phone number appended to the black tile. As such, the asymmetries created by this technology may, despite the well-meaning of judges, subtly affect their impressions, empathy, and motivations. These affordances and barriers will alter the judicial role.

Motivation. The shift from in-person proceedings to Zoom virtual hearings may affect the motivation and goals of judges and court personnel who operate under severe resource constraints. While courts have shifted to a therapeutic or problem-solving orientation when addressing in-person cases, including evictions,Footnote ⁵² the shift to Zoom court may affect this orientation. When low-income unrepresented persons dial into a Zoom virtual hearing, they appear as black Zoom tiles with a phone number (or merely a case ID), and this may hinder the empathic concern necessary for a therapeutic or problem-solving orientation.

Perception and impressions. Video-mediated communication alters the way people are perceived and the impressions formed.Footnote ⁵³ In this context, unrepresented persons who appear in Zoom virtual hearings via video, rather than in person, may be perceived as less warm and competent than those who appear in person, especially relative to the lawyers who appear virtually in court.Footnote ⁵⁴

Cognitive depletion. “Zoom fatigue” is depleting because video conferences are cognitively demanding, requiring one to “focus more intently on conversations in order to absorb information,” as opposed to the nonverbal cues we usually rely upon.Footnote ⁵⁵ Relatedly, Zoom participants have the ability to watch oneself during these video conversations. Yet seeing one’s own video generates a state of objective self-awareness, which may increase the cognitive load of engaging in these technologies, and may impact a person’s interactions in a videoconference.

Empathy. These technologies also affect the empathy expressed and experienced. Facial expressions, gaze awareness, and nonverbal behaviors build trust and empathy between people, and they affect person-perception as well. When these technologies interrupt or conceal these nonverbal behaviors, empathy may be reduced. For example, the video framing of cell phones (if video is available at all) and a stable mounted computer will have different effects on the inducement of empathyFootnote ⁵⁶ because the video framing of stable mounted computers may capture these nonverbal features of the upper body and correct for gaze error. Moreover, empathy is more easily generated between people who have ongoing relationships or frequent conversations; thus, strangers are at a distinct disadvantage when presenting over video.Footnote ⁵⁷

Digital inequalities between lawyers and many low-income unrepresented persons may translate into disparities in the ability to gaze at the judge during these virtual hearings. Gaze awareness is an important factor that affects whether people are perceived as generally interested, trustful or approving, or attentive.Footnote ⁵⁸ Gazing is an important expression of interpersonal attitude or affect. Indeed, lawyers are taught to gaze in order to enhance their persuasion,Footnote ⁵⁹ ingratiate themselves to the judge and jury,Footnote ⁶⁰ or assert dominance over opposing witnesses and parties.Footnote ⁶¹ Because those who dial into these Zoom proceedings are unable to gaze at the judge or opposing lawyer, they may be construed as being “defensive” or “evasive.”Footnote ⁶² Moreover, eye contact is an important ingredient to social interactions and may prompt recursive processes of trust and rapport, whereas an inability to gaze may generate distrust and harm rapport in intergroup encounters.

The increased psychological distances that these technologies create may lead to depersonalization or, in the worst scenario, dehumanization.Footnote ⁶³ This may be in part because these technologies may shape the way others are construed: whether they are construed more abstractly or individuated, whether they are experienced as close or far,Footnote ⁶⁴ which may impact depersonalization. The risk in the scenario at hand is that low-income unrepresented persons who dial into these Zoom virtual hearings may be depersonalized, that their appearance in a Zoom tile with a number and a disconnected voice may subtly dehumanize them in the eyes of the court officials and lawyers.

Behavior. At least two studies suggest that Zoom virtual hearings may elicit faster interactions and decisions than in-person hearings. That is, that the discrete hearing time is faster than would otherwise be the case because of the social-cognitive dynamics produced by the technology employed. This was observed, for example, in the impact of videoconferencing in judicial decision-making about deporting immigrantsFootnote ⁶⁵ and is documented in research on the effect of videoconferencing on team performance.Footnote ⁶⁶

Contingent nature of the judicial role. Interactions between judges, lawyers, and unrepresented persons and their performances in the courtroom are contingent on the technologies employed within the civil justice system.Footnote ⁶⁷ These court performances are shaped, in part, by the technological capital of these various actors.Footnote ⁶⁸ For example, Rowden and Wallace, in studying the introduction of videoconferencing in Australia, found that the introduction of this technology had “a profound impact on the production, management and consumption of judicial images, [which] has implications for the judge’s in-court role both as traditionally conceived and in practicing new types of therapeutic jurisprudence that require increased emphasis on engagement with other court participants.”Footnote ⁶⁹ In general, virtual hearings are associated with more distant or impersonal communication. Yet the introduction of these technologies has occurred at a time when there has also been a strong move toward more engaged styles of judging.Footnote ⁷⁰

10.5.2 Lawyer’s Perspective

Like the judge, but unlike low-income persons who dial into these Zoom hearings, a lawyer will be able to see and be seen by the judge. This will affect their adversarial orientation and potentially exacerbate asymmetries against unrepresented people. These asymmetries may affect opposing lawyers, who are in an adversarial orientation, making it more likely for them to use nonverbal behaviors and documents that unrepresented people are unable to see. It may also lead them to dehumanize these unrepresented persons.

Initial face-to-face interactions and preexisting relationships. Initial face-to-face meetings are crucial for enhancing later virtual interactions.Footnote ⁷¹ Research on distributed teams in the business context reveals that conflict is mitigated by in-person meetings followed by regular video conferences, which can help to maintain a cohesive team and a sense of shared identity. One leading study noted that people who met in person before video-mediated meetings were better at establishing trust with other group members than those who had not met beforehand.Footnote ⁷² Another likewise found evidence that initial in-person contact could benefit later virtual conferences.Footnote ⁷³ This research suggests that video conferences may be more effective for lawyers who are already acquainted with judges and have preexisting relationships with them.

10.5.3 Unrepresented Person’s Perspective

Finally, unlike judges and lawyers, an unrepresented person who dials into a Zoom hearing cannot see or be seen, and they appear as a black Zoom tile on the judge’s and lawyer’s computer screens. This may affect their participation, experience of justice, and the outcomes obtained.

Construal and meaning-making. When low-income unrepresented persons dial into Zoom virtual hearings, they have access to audio-conferencing capabilities only and are unable to see a courtroom at all. This will undoubtedly affect the sense of realism, solemnity, and gravity of the proceedings, when compared to in-person or videoconferencing enabled proceedings. This may leave them apathetic or confused, experiencing the process as less “real.” Moreover, friction and barriers accessing these Zoom virtual courtrooms may lead unrepresented persons to infer that these virtual court proceedings are not truly designed for people like them.

Experiences of procedural justice. Research suggests that in-person participation may be perceived as more procedurally just than technologically mediated participation.Footnote ⁷⁴ For example, research in organizational justice has concluded that applicants were less attracted to organizations that used video interviews compared to in-person interviews.Footnote ⁷⁵ Other studies have noted that in-person interviews were regarded as fairer than video-mediated interviews, resulting in higher levels of job acceptance.Footnote ⁷⁶ In still another study, interviewees rated their interviewers as less friendly during the video-mediated interviews (in comparison to in-person and telephone interviews).Footnote ⁷⁷ This research suggests that some unrepresented persons may experience videoconference proceedings as less procedurally just than in-person proceedings. Extrapolating this research a step further, one can infer that unrepresented persons may find it procedurally unjust to be limited to audio-only capabilities when their adversaries have access to the full range of video-conference capabilities.

Relational feedback, turns, interruptions. Physical proximity supports the interaction and cohesion of groups.Footnote ⁷⁸ This is, in part, because of bandwidth and network cost limitations that reduce the rate, clarity, and frequency of communicative turns.Footnote ⁷⁹ Because low-income unrepresented persons are unable to observe or communicate with nonverbal behavior, this may exacerbate miscommunication, while at the same time making judges, lawyers, and unrepresented persons slower to correct these misunderstandings.Footnote ⁸⁰ Indeed, we observed several instances in which this kind of miscommunication occurred for unrepresented persons who were not proficient in English. Unfortunately, these unrepresented tenants dialed into Zoom court and were not able to overcome the language barrier. Similar issues may occur for persons with disabilities, though virtual proceedings may also increase access for persons with mobility-impairing disabilities as well.Footnote ⁸¹

One challenge is that these faster hearing times may be coupled with more problematic intergroup interactions. The asymmetries in these interactions may harm intergroup interactions in virtual environments. For example, many judges and lawyers are majority group members, while many low-income members are racial or ethnic minorities or belong to vulnerable groups. Past research has found that an audiovisual lag in an interaction may incite tension in intergroup interactions, particularly when persons are not well acquainted.Footnote ⁸²

Participation. If unrepresented persons experience the process as procedurally unjust, their participation and engagement may be dampened. Indeed, researchers have suggested that videoconferencing technologies may have prompted declines in participation, which may have explained adverse outcomes in research involving bail decisionsFootnote ⁸³ and immigration removal decisions.Footnote ⁸⁴

Contingent nature of unrepresented persons. Finally, these technologies and the digital inequalities engendered reveal the contingent nature of being a self-represented litigant in the civil justice system. As has been described, the very act of appearing in court is altered and dependent on the technologies employed within these proceedings. At the same time, this technology may benefit the most advantaged unrepresented persons who have technological capital, capacity, and wherewithal. Technological capital is a subset of, and an addition to, Pierre Bourdieu’s cultural, economic, and social forms of capital in the information age,Footnote ⁸⁵ marked by first-order and second-order digital divides in internet access, skill, and experience.Footnote ⁸⁶ These societal patterns may, in part, explain why so many unrepresented persons dial into Zoom virtual hearings from their cell phones without videoconferencing capabilities.

11.1.1 Public Enforcement in “Simple” Cases

With respect to public debts, the Department of Justice Investigation of the Ferguson Police Department and follow-on litigation against municipal courts around the country show that there has been widespread abuse of legal financial obligations as cash-strapped municipalities deprived of general funds by their states have converted courts into fee-for-service systems parasitic on the most financially vulnerable populations within their jurisdictions. In Ferguson, excessive fines and fees were imposed disproportionately on the African American population of the city. The Report’s section on the court system found that enforcement actions involved shocking deviations from basic principles of procedural due process, including failure to make the constitutionally required inquiry into litigants’ ability to pay before using imprisonment as a penalty or inducement for nonpayment.Footnote ⁴⁹ Litigation in dozens of other jurisdictions reveals that the problems with setting and collecting legal financial obligations are widespread.Footnote ⁵⁰ One report revealed that the

“Tragic incidents such as these draw into vivid relief the human cost of ignoring the connection between procedural due process and human dignity”.

As local courts have faced funding crises and failed to address racial bias, advocates of ODR have been marketing their platforms to court systems around the country and in the pages of law reviews by packaging enhanced efficiency in collecting public debts in the language of “access to justice.” ODR advocates insist that in traffic cases faster, cheaper resolution benefits individual defendants because they get closure and avoid the additional fees associated with failure to appear and default.Footnote ⁵² But when one examines the use of the platforms marketed to court systems, one finds things like the Fort Collins, Colorado, municipal court’s ODR system for “camera radar/red light tickets.”Footnote ⁵³ The ODR system provides for resolution of traffic camera tickets.Footnote ⁵⁴ The sophisticated cameras cost $10,000 a month each to operate. Tickets are $75.Footnote ⁵⁵ The city claims that the cameras are making a “huge difference” in driver education and safety, and it points to data showing reductions in accidents at one of the intersections where the cameras are used.Footnote ⁵⁶ But the program also reportedly nets the city about $200,000 a year over operating costs, including payments to the private contractor who services the cameras.Footnote ⁵⁷ Camera citations well exceed officer written traffic tickets in the city, and in other jurisdictions there is evidence that this enforcement tool invites politically corrupt outsourcing to private contractors and generates revenue without improving traffic safety at all.Footnote ⁵⁸

The Fort Collins ODR system does not appear to follow a pure bargaining model where the resolution results from negotiating what will be paid irrespective of the merits. Nor, however, does it appear to be designed to fully and faithfully ascertain the merits in each case, including educating defendants about how to explore and assert standard defenses. The defendant is assured there is a prosecutor who will review the case and the website’s “About Online Case Review” page indicates that a defendant could “potentially have … fines and fees reduced or in some cases, dismissed altogether.”Footnote ⁵⁹ The FAQ page, however, characterizes ODR as a process to enter a guilty plea through an “Online Plea” process.Footnote ⁶⁰ The page indicates that “You can plead guilty, be sentenced, and pay your fines/costs without going to court in person.”Footnote ⁶¹

If the system is mainly designed to enter guilty pleas and collect the fines and fees – if, that is, the private “review” conducted by prosecutors and the court is perfunctory, designed to “improve compliance” on the same terms as the designer’s platforms sold to other jurisdictionsFootnote ⁶² – then the efficiency gains accrue mainly to the city.Footnote ⁶³ In cases where guilt is unclear or revenue generation dominates public safety priorities, defendants are saddled with unwarranted debts and the public with rent-seeking law enforcement. Indeed, a compliance-oriented ODR system that primarily increases the speed of collection for traffic camera fines raises the specter of fully automated law enforcement in derogation of every procedural value other than reduced cost to the state.Footnote ⁶⁴ Nor does such an ODR enforcement process provide a public forum, as court proceedings do, for airing systemic concerns about whether revenue generation dominates legitimate public safety concerns. Public and media scrutiny of enforcement is literally short-circuited.Footnote ⁶⁵

Remarkably, ODR advocates commonly ignore or suspend the merits question altogether – either not seeking to measure it, excluding it from the design of ODR systems, or both.Footnote ⁶⁶ Traffic cases are indeed minor relative to felony cases, but the lesson of Ferguson and broader litigation about excessive fines and fees is that incursions on civil liberty and civil rights in the design of dispute resolution systems for these offenses can be substantial. Recent scholarship on criminal law and procedure reinforces this conclusion, showing that twenty-first-century misdemeanor enforcement has been used to criminalize poverty, to impose onerous systems of regulation and continuing supervision on marginal populations, to feed mass incarceration, and to subordinate racial minorities through biased forms of “order maintenance,” policing, and punishment.Footnote ⁶⁷ To submerge these distortions in the administration of justice in automatic collection-compliance processes would obviously be inconsistent with the mission of enhancing access to justice for ordinary people.

11.1.2 Private Enforcement in “Simple” Cases

Even when the state is not a party to supposedly “simple” cases, recent empirical studies show that the simplicity hypothesis is untethered from the realities of the administration of justice. As ODR advocates describe small claims, it would be easy to assume not only that private individuals are on both sides of the litigation, but that in many “simple” cases people gin up “highly emotional conflicts over matters with relatively low monetary value.”Footnote ⁶⁸ This happens, to be sure, but the data show that far more often an individual unrepresented defendant is sued in small claims court by a powerful creditor or landlord represented by counsel. The greater leverage of these plaintiffs is mobilized not to force costly merits adjudication, but rather to accelerate reduction of a claim to a final judgment and proceed with enforcement.

The National Center for State Courts Landscape of Civil Litigation study in 2015 found that three-quarters of all judgments in the state courts were less than $5,200.Footnote ⁶⁹ Even among non–small claims cases that went to trial, “[t]hree quarters of judgments entered in contract cases following a bench trial were less than half of those in small claims cases ($1,785 versus $3,900). This contradicts assertions that most bench trials involve adjudication over complex, high-stakes cases.”Footnote ⁷⁰ Whatever the nature of modern trial, most civil cases, the study emphasizes, were “disposed of through an administrative process,” and for cases that reached judgment, the most common resolution was a default judgment.Footnote ⁷¹ In these cases, then, there is no meaningful deliberation on the merits, often no hearing whatsoever preceding the entry of judgment.

Most revealingly, the Landscape Study found that

The conjunction of self-representation and default judgments in small value debtor-creditor disputes suggests that some state courts are operating as accelerated debt collection forums. In the forty-four states where judges, clerks, magistrates, and justices of the peace are allowed to issue capias warrants for failure to appear at post-judgment asset examination hearings, defendants in civil cases face arrest and incarceration with bond often set equals to the debt owed.Footnote ⁷³ As with misdemeanor criminal cases then, civil litigation for people in financially precarious situations can result in restraints on liberty in order to force payment.

On this evidence, as with the use of ODR for misdemeanor cases and legal financial obligations to courts, the simplicity/access nexus looks quite ominous. The access-to-justice problem is not how to speed things up and substitute automated bargaining over settlement value (or private deliberation on facts adduced through strictly circumscribed online submissions) in place of public inquiry into the merits in small value cases. It is (1) how to slow creditors and other repeat players down in order to ensure attention to the merits and (2) how to address the systemic disparities in power that shape both the debts being collected (click-wrap and other contracts of adhesion; payday lending schemes, etc.) and enforcement procedures (default judgment, capias, etc.). ODR systems oriented toward speed and automated online resolution may be quite attractive to plaintiff creditors and other repeat players, but for individual defendant debtors, the risk is great that ODR systems will not include adequate exploration of defenses available under the relevant contract, lease, or state and federal consumer protection and fair debt collection practices laws.Footnote ⁷⁴ These defenses are not generally regarded as “simple” by experts. A 2010 FTC report found that even basic affirmative defenses such as state statutes of limitations “on filing actions to recover debt are sometimes variable and complex, and generally not understood by consumers.”Footnote ⁷⁵ An allegation of identity theft raised by a debtor can “increase the complexity and time required” to resolve a matter.Footnote ⁷⁶ The Truth in Lending Act’s enforcement structure – which contemplates use of the statute as a counterclaim in a debt collection proceeding – is famously “confusing.”Footnote ⁷⁷

Enough has been said, I hope, to make clear that small values cases are by no means simple or low stakes either for the parties concerned or the administration of justice. Nor are these cases small in number – they compose a substantial part of court dockets and therefore of the cases handled by the adversary system. The simplicity hypothesis is false. If there is a class of truly simple claims suitable for ODR, the hard question is how to define standards for accurately identifying them without having to adjudicate the merits along the way – the very task the avoidance of which makes ODR so affordable. As matters currently stand, then, the principal effect of using low money-value claims as a proxy for simplicity will be to produce a bifurcated system of justice – one in which low- and middle-income people already priced out of meaningful participation in the adversary systemFootnote ⁷⁸ will have no alternative but to avail themselves of ODR systems. This bifurcation in the administration of justice will merely formalize, encode and multiply, not mitigate, problems of access to justice.

In the most ambitious ODR systems – those that remove the third party neutral human decision-maker altogether – low- and middle-income people will receive justice defined by software engineers unregulated by standards of judicial ethics except to the extent that courts supervise their outsourcing contracts. And we know that supervision will be limited by the fact that the best AI systems to date are opaque in their operation even to their designers.Footnote ⁷⁹ So, for instance, a deep learning system used to generate “reasonable” settlement values might not be explainable – even by the engineers who program it. Systems that are more transparent because they rely on expert design rather than deep learning, on the other hand, remain highly reductive.Footnote ⁸⁰ Absent regulation, this bifurcated system for the administration of justice will flourish on terms that limit assessment and accountability.

11.2.1 ODR’s Design Features

Although the overall ecosystem is heterogenous and evolving rapidly, most current ODR platforms function by breaking dispute resolution into its component phases, reducing legal forms and rules to plain language questions, instructions, and guidance, and then using asynchronous electronic communication, document storage, retrieval, and review to facilitate the flow of information needed to define and resolve the dispute, as shown in Table 11.1.

In the first phase there is typically a webpage with plain language text, videos, and graphical information describing the specific ODR process. In some instances, general information on the law is provided (at varying levels of detail). In others, there is little or no information about the underlying rights and defenses that apply to the dispute or resources for ascertaining what the law is. The emphasis is instead on identifying the parties’ interests. Rechtwijzer, the Dutch online ODR system that, until its demise in 2017, handled divorce, family law, debt, and neighbor disputes, explicitly encouraged the parties to approach the process through the framework of interest-based resolution.Footnote ⁸¹ Divorcing parties were initially informed of “rules such as those for dividing property, child support and standard arrangements for visiting rights so that they could agree on the basis of informed consent,” but the software’s negotiation framework prioritized interests, not rights.Footnote ⁸²

British Columbia’s vaunted Civil Resolution Tribunal (CRT) includes a statute-of-limitations information page that defines what a statute of limitations is and advises parties that it is not tolled during the first phases of the CRT process. But it does not answer the question of what statute of limitations applies to the dispute the party has, how to determine either when it started to run, or when it will expire. The page ends with the statement: “We can’t answer these questions for you. You may want to get legal advice. The CRT can’t provide legal advice.”Footnote ⁸³ Indeed, CRT’s detailed downloadable forms to help parties prepare for negotiation generally ignore rights and defenses, instead prompting the parties to identify and articulate their interests.Footnote ⁸⁴

To generate enthusiasm and induce users to opt in, introductory pages of ODR websites also include substantial promotional content highlighting perceived advantages of ODR relative to adjudication in court. The CRT home page begins: “Save time, money, and stress! The CRT lets you resolve your dispute when and where it’s convenient for you …. The CRT helps you resolve your dispute quickly and affordably.”Footnote ⁸⁵ Rechtwijzer, the online divorce settlement platform, billed itself as providing a chance to “separate together” without the adversity and acrimony of divorce in court.Footnote ⁸⁶ ODR websites generally do not counterbalance their self-promotion regarding the advantages of online resolution with sober assessment of potential downsides, clear notice about rights waived, or alternatives.

In Phase II, once users have opted in, questions are directed to the users through a range of graphical interfaces in order to gather basic information about the dispute, classify it, populate relevant forms, and upload relevant documentary evidence. Advanced systems use chatbots or other interfaces modeled off of apps people use daily on their smartphones and other devices. Matterhorn, the ODR system behind the Colorado traffic camera enforcement discussed in Section 11.1 has an online process for “the uploading of statements by parties, law enforcement and court personnel from afar and in lieu of court hearings.”Footnote ⁸⁷ In this phase, assuming the design for information sharing is not reductive, there are obvious efficiency gains in cost, time, and convenience associated with “asynchronous processes” for fact gathering relative to filing papers in court.Footnote ⁸⁸

In the negotiation phase, Phase III, there is a wide range of approaches. Some, such as CRT’s, simply provide online portals for direct, unmediated negotiation between parties with some basic ground rules about abusive communication and guidance about how to prepare and conduct a successful interest-based negotiation. Others introduce a human third-party neutral to guide negotiation. Still others are automated and more rigidly structured, channeling the parties into online negotiation in the form of blind bidding with an algorithm that is designed to identify an optimal settlement from the highest one party is willing to offer and the least the other is willing to accept.Footnote ⁸⁹ This ostensibly allows parties to “overcome tactics often employed in face-to-face negotiations that hinder reaching an agreement despite the existence of a ‘zone of possible agreement.’”Footnote ⁹⁰ Smartsettle’s software forces parties to “list their interests and assign numerical values to them, thereby creating a weighted spectrum of issues” from which an algorithm “generated various ‘packages’ or combinations of issues that might satisfy both parties” along with “a graph as a visual display of the level of satisfaction each package of issues represented for the parties.”Footnote ⁹¹ Overall, both public and private ODR platforms share some of the following algorithmically automated features at varying levels of sophistication: “identifying dispute types; exposing parties’ interests; asking questions about positions; reframing demands; suggesting options for solutions allowing; allowing some venting; matching solutions to problems; and drafting agreements.”Footnote ⁹²

In the phase IV, a third-party neutral human expert may be brought in online to review and approve a deal reached between the parties. This was the case with Rechtwijzer. If online negotiations resulted in an agreement, an independent lawyer would be brought in to review the deal “to ensure that it meets legal requirements and is fair to both parties.”Footnote ⁹³ If no agreement was reached, a mediator or arbitrator would be brought in online to help facilitate resolution. Costs were a fraction of traditional costs for counsel in divorce proceedings in court, and “[e]ven at the higher end,” costs were “lower than the costs to the Legal Aid Board for representing both parties to divorce proceedings in court.”Footnote ⁹⁴ In the near future algorithms may not only structure negotiation and suggest solutions but displace the third-party neutral altogether by using artificial intelligence to review and validate negotiated solutions.Footnote ⁹⁵

In the fifth and final phase, an agreement reached online is reduced to an enforceable contract or court order. Generally, ODR negotiations cannot be introduced in court, but there are many exceptions. CRT participants, for instance, lose confidentiality if they use what the system designers determine is “abusive” language in settlement negotiations. ODR websites also vary widely in the promises they make regarding the use of user data (information such as identity, location, negotiation documents and communications, history of participation in ODR or other litigation, etc.), sale of such data to third-party data brokers, and how and on what terms such information is shared with court systems with whom they contract and other government entities. Generally, there is no public access to the ODR process in real time, no public ODR docket, and unlike codes of procedure and evidence in courts and the decisional law interpreting them, the lines of code in ODR systems are proprietary, insulated from public review, and treated as trade secrets by ODR companies.

11.2.2 ODR as Interest-Based Dispute Resolution

What can be inferred from this structure about ODR as a form of dispute resolution? What theory of justice does its architecture embody? The most important thing to notice is that the overwhelming emphasis in the structure of ODR systems is on “integrative negotiation” or interest-based, win-win bargaining, rather than the merits.Footnote ⁹⁶ The “archetypical ODR approach is to provide an online forum and tools to facilitate the full settlement of claims without any human intervention.”Footnote ⁹⁷ However, users unfamiliar with law are not in a position to recognize that ODR is oriented toward integrative resolution rather than resolution based on their legal rights and defenses.Footnote ⁹⁸

Although even the earliest theories of interest-based negotiation insisted that interests must be “legitimate” to warrant consideration, and that “community concerns” are relevant to bilateral negotiation,Footnote ⁹⁹ some ODR systems eliminate these factors entirely. Blind bidding and other mathematical representations of interests have this effect – resolution arises from overlapping settlement values defined by the parties irrespective of any independent assessment of how the merits relate to the parties’ quantification of their interests. In other ODR systems, such as CRT and Rechtwijzer, attention to the legal merits and third-party effects is backloaded into the review phase (phase IV) when a third-party neutral steps in. But at that stage, rejection of a settlement entails losing the efficiency gains accumulated through the ODR negotiation process. Delayed intervention of the third-party neutral thus virtually guarantees the subordination of concerns about the merits and negative externalities imposed on third parties and the community. The prize of agreement, once reached, is exceedingly difficult to refuse. As importantly, fact development to that point may not illuminate defects even for a third-party neutral deeply comitted exercising independent judgment and disposed to resist the allure of the prize.Footnote ¹⁰⁰

Even systems that bring a third-party neutral in earlier may not improve attention to the legal merits. As the orientation of many third-party neutrals is toward efficiency, “harmony and overcoming conflict,” not the legal merits,Footnote ¹⁰¹ their disposition, training, and docket pressure may lead the them to “‘trade justice for harmony.’”Footnote ¹⁰² This has long been a criticism of the alternative dispute resolution movement, sharpened by evidence that by privileging “harmony” in pluralistic societies (where there are competing conceptions of the good and systematic marginalization of minority groups), interest-based resolution can “suppress … or silence … the voices of those without political power.”Footnote ¹⁰³ In cases involving public debts to courts, revenue generated from these cases may diminish impartiality, attention to the merits, and community concerns. Some ODR systems are marketed to courts on precisely these terms, touting increased collection rates, decreased defaults, and reduced time to collection. For example, Matterhorn’s contract with the court in Washtenaw County, Michigan, for traffic violations helped the company expand ODR to dozens of other counties on the back of reports that it produced a more than 40 percent increase in fines paid within thirty days.Footnote ¹⁰⁴

Although facts can generally be elicited efficiently online relative to live hearings and paper filings, important information can be lost in shifting from a hearing/forms combination to text-only,Footnote ¹⁰⁵ writing skill is a built-in advantage for high-literacy litigants,Footnote ¹⁰⁶ and without tailored advice about how the law applies to the facts of their case, litigants may omit relevant evidence. Everything hinges on how questions posed to elicit the facts are framed by the ODR platform. On the other hand, the more detailed the questions and guidance, the more expensive the code. Even the most advanced current AI systems thrive in bound environments, not open-ended, indeterminate ones.Footnote ¹⁰⁷ The temptation, therefore, is ever to manufacture a bounded environment in coding for dispute resolution – reducing complexity in order to code efficiently.

Modria’s brochure for courts considering adoption of its ODR software, proudly declares that it “helps courts resolve all manner of case types faster without sacrificing accuracy,” but if we take the architecture of ODR systems seriously, the truth is that it is quite difficult to assess the accuracy of ODR systems.Footnote ¹⁰⁸ Indeed, the earlier cases settle and the more interest-based bargaining drives resolution, the less certain we can be that any given settlement is a just reflection of the relevant rights and defenses of the parties.Footnote ¹⁰⁹

11.2.3 ODR Funding

Funding remains one of the greatest barriers to the development of ODR and, ironically, one of the weakest pillars in its claim to expand access to justice. Many systems have failed because they have not produced a durable financial model despite receiving public subsidies and favorable user reviews.Footnote ¹¹⁰ The systems are costly to develop, and both the law and technology change in ways that make it costly to keep the systems up-to-date. One prominent provider, CRT, therefore relies heavily on a fee-for-service model. The parties using CRT pay not only initial filing fees, but fees for every subsequent phase of the process, making the process more expensive as it unfolds if no negotiated solution is reached.Footnote ¹¹¹ CRT also charges a substantial fee ($200) to file a notice of objection in a small claims dispute.Footnote ¹¹² This means that for a small claims dispute involving $1,000, challenging a settlement would cost 20 percent of the value of the dispute (on top of $75 to file the complaint, $75 to add a claim against a third party, $10 per records request, and $50 to switch from negotiation to an adjudicator).Footnote ¹¹³ Fee structures like this induce people who have financial constraints to resolve disputes quickly and accept a resolution that may be unjust. People of means, on the other hand, can afford to take advantage of every avenue of relief.Footnote ¹¹⁴

Other ODR systems are free to usersFootnote ¹¹⁵ and presumably paid for by courts. Contract terms between courts and private vendors of ODR software are not generally available to the public.Footnote ¹¹⁶ This makes any comparison with the costs of alternatives to ODR such as civil GideonFootnote ¹¹⁷ difficult to assess. It also contrasts sharply with the public budget process of funding courts as well as rules of judicial ethics that strictly regulate financial conflicts of interest in the judiciary.

11.2.4 ODR Party Structure

Although the ODR literature focuses on small value civil law disputes between roughly equally situated, unrepresented private parties, ODR is currently being used for disputes that involve parties of radically unequal status. These include criminal disputes between the government and individuals, where ordinary people are negotiating with prosecutors and judges regarding fines and fees the nonpayment of which could lead to incarceration, disputes between landlords and tenants, property associations and owners, creditors and debtors, contractors, subcontractors and home owners, nonunion employees and employers, insurers and parties harmed in an accident,Footnote ¹¹⁸ and couples who brought vastly different resources into the marriage and are unequally situated.Footnote ¹¹⁹ Some ODR systems permit parties to be represented if they can afford to do so, introducing potentially vast disparities in the level of expertise that one side brings to negotiations. Experience with other ADR systems such as arbitration is sobering on this front, indicating that powerful repeat-players not only fare better but are able over time to shape ADR procedures to maximize their interests.Footnote ¹²⁰ Nor do the opt-in pages of ODR systems adequately disclose information to support knowing and informed waivers of due process rights and other rights a party would have in court.

In sum, democratically enacted and public rules of procedure and evidence are displaced by the proprietary technology of ODR systems.Footnote ¹²¹ Lawyers who work in principal-agent relationships for clients, and who have expertise in the rules of procedure and evidence, are replaced by software engineers whose highest loyalty is to investors and, secondarily, to the courts who retain them to help reduce costs. There is no malpractice cause of action for users against ODR providers, and no enforceable ethical code requiring fiduciary duty, competence, diligence, loyalty, communication, or confidentiality. Users of ODR platforms, who are constitutional right holders in the adversary system, become mere tertiary beneficiaries of contracts entered between courts and ODR providers. And as with other forms of alternative dispute resolution, ODR replaces the public appearance and reason-giving function of the judge either entirely (in systems that displace these decision makers with AI) or partially by changing the scene of adjudication from a public courtroom to a private online forum where third-party neutrals facilitate or impose resolution behind encrypted walls of code. We know that the reasons for conducting adjudication publicly in adversarial space are not exclusively performative.Footnote ¹²² Doing so helps prevent corruption, bias, and arbitrary decision. Justice, the saying goes, must not only be done, but must be “seen to be done.”Footnote ¹²³

No one should therefore be surprised to see ODR systems that serve principally to induce settlement and improve compliance with judgments on behalf of the state, powerful creditors, and other well-resourced, represented parties, while failing either to establish the rights and defenses of unrepresented parties or make transparent potentially systemic abuses of the laws being enforced.

12.1.1 Where the Story Begins: Courts, ODR, and Access to Justice

Less than ten years ago, state courts began implementing ODR platforms for high-volume, small-stakes cases, like alleged traffic violations and other cases where physical resolution of the matter could be very costly to one of the litigants (e.g., outstanding failure-to-pay warrants), making remote resolution particularly attractive. One of the very first ODR platforms, if not the first, to be widely adopted in US courts was Matterhorn, which Michigan adopted starting in 2014.Footnote ²²

The earliest Matterhorn ODR implementations sought to resolve disputes between individuals and the government: traffic, civil infractions, warrants, and a couple of misdemeanors. These ODR platforms were in many ways designed to “mimic” traditional proceedings, with a few key differences: ODR was made available at any time of day, information was exchanged asynchronously by text, and litigants could access the platform with any online remote device. But in most respects, litigants could expect to experience a process similar to going to court on their own. These systems inform the litigant of the charge or issue, “ask” the litigant whether they would like the court to review their case, and then ask the litigant to answer questions, including an open-ended invitation to “let the court know” anything else they felt was potentially relevant. These implementations are easy to use and make the process much easier to follow than what a litigant walking into a courthouse should expect to face, but at their core, they are an online version of a pro se courthouse experience.Footnote ²³ The individual locates their case, makes a request for relief, and answers questions from the court.Footnote ²⁴

Matterhorn ODR soon grew to address disputes between private individuals. Early examples include ongoing family court cases, where parties negotiate in the online presence of a case manager without the need for in-person hearings,Footnote ²⁵ and small claims disputes, where parties use an online text-based negotiating (chat) space (and perhaps online mediators) to engage in informal discovery or settle their case outright. These ODR implementations sought to reduce default by making it easier for everyone to come together outside of court in an informal way before being compelled to come together in court. Parties usually negotiate a resolution, and by making online negotiation and mediation free, easy to use, and court-sanctioned, courts were soon playing an important role via ODR in a significant fraction of cases. What’s more, some tentative evidence hints that early engagement with court-connected ODR promotes traditional courtroom engagement later, which might have social benefits,Footnote ²⁶ even if a case ultimately ends in face-to-face litigation.

Regardless, first-gen ODR works by moving courtroom or court hallway activity to a more amenable online venue that can be streamlined/individualized for the type of case. A pro se litigant may find it easier to negotiate with a counterparty or contest a civil infraction through an ODR platform, but such litigants are just as “pro se” during an online interaction as they would have been during an in-person tête-à-tête.Footnote ²⁷ Whether first-gen ODR moves into asynchronous text-based exchanges or real-time video-based hearings (or any number of other ways parties can communicate, make offers and demands, share/present information, and work through outcome-determinative decisions), existing ODR platforms can make dispute resolution easier, faster, cheaper, and therefore more accessible, but the value of legal advice is likely to matter just as much as it does in traditional settings. True, more “have-nots” will be able to use courts and access the law. But the “haves” (with their lawyers, experience, and mastery of the rules of the game) will remain just as privileged (if not more so, given digital divide concerns) relative to their “have-not” counterparts as before.

Empirical evidence on ODR outcomes is consistent with this story. This expanding literature speaks to the improvements enjoyed by pro se litigants (as opposed to represented parties): Cases proceed more quickly, default rates plummet, and communication between parties, court staff, and judges increases.Footnote ²⁸ This accessibility leads to more accurate outcomes (primarily by reducing default), giving more muscle to substantive law and reducing the role litigation costs play in determining legal outcomes.Footnote ²⁹ In the case of Matterhorn, at least, litigants also report that they find ODR proceedings fair, the online process easy to understand, and the software straightforward to use.Footnote ³⁰ On the whole, ODR-based improvements in pro se litigant outcomes (both quantitative and qualitative) appear significant, although these advances are relative to a pro se baseline where the relevant control groups of litigants are also unrepresented.

12.1.2 From Courtrooms to ODR: Responding to Critics

Moving from courtrooms to ODR is no panacea, of course. Critics raise a number of concerns, including the importance of the courtroom and human interaction in how litigants experience justice, the ability of efficiency-oriented designers to reduce choice and induce compliance, the lack of transparency in ODR hearings, the rigidity and inflexibility of procedures, and many others.Footnote ³¹ Most of these complaints, however, focus less on ODR’s basic principles and more on the weaknesses critics observe in specific first-gen systems.Footnote ³² Like traditional procedures, ODR will only be as good as its design. Yet ODR’s inherent flexibility gives courts the means to resolve many worries raised about existing systems, if they have the will: for example, all ODR-related policies, choices, and outcomes can be made public, and the workflow can be designed to maximize litigant voice, even if current instances of ODR score poorly on these measures. Furthermore, ODR is almost always an option, not a requirement, so those who object to ODR must defend disallowing low-cost access alternatives for litigants who retain more expensive “Cadillac” access to justice and yet prefer ODR when given a choice.Footnote ³³

More importantly, most criticisms fail to reckon with the very real problems of traditional adjudication, especially in low-stakes cases. Detractors compare ODR processes to a stylized and idealized version of traditional adjudication.Footnote ³⁴ But this perspective ignores the existing brick-and-mortar system’s huge access-to-justice issues – including regressive costs, biases, disparities, confusion, and intimidation – as well as the paper-thin procedures that many if not most litigants experience in courtrooms. These critics compare the best of courts to the worst of ODR.

Some criticisms rightly focus on ODR being peddled by the private sector and the implications of long-term profit motives.Footnote ³⁵ But there is nothing inherent in ODR as a concept that requires deferring to a private vendor; courts can and do build their own ODR systems (albeit, often via work-for-hire, which is par for the course when it comes to government software adoption). There are potentially negative, more indirect consequences to making courts and the law easier to access, too. Once lawsuits are extremely easy to file, answer, and navigate, more disagreements will become lawsuits. While ODR can be designed to balance access costs for plaintiffs and defendants, for instance, it may actually increase litigation rates. But the argument that making courts more efficient and accessible in a party-neutral way might be socially problematic simply proves too much; a corollary would be that courts ought to move back to pen-and-paper orders and file cabinets.

12.1.3 Auguries: First-Gen ODR and the Representation Gap

With respect to pro se litigants and the “representation gap,” at least some evidence suggests that ODR systems, even first-generation ones, can level the playing field just as retaining legal representation does. For instance, ODR proceedings in the traffic context are associated with fewer race- and age-based disparities, either because switching to online proceedings (for example, text-based, asynchronous communication or at-home, video-based hearings) differentially benefits some groups over others or because ODR platforms reduce implicit bias by limiting decision-maker exposure to legally irrelevant identity traits.Footnote ³⁶ The precise mechanism here is unclear, but this reversal is important and ties into questions about the benefits of corporeal representation in court. Lawyers “represent” their clients and so may disrupt implicit biases or other cognitive/behavioral distortions that attach to litigants who appear in person on their own. ODR may do this, too. At the same time, by offering litigants an alternative to a single, one-size-fits-all track, any single limitation a litigant might have in, say, communication (e.g., difficulty speaking in open court) is less likely to matter. In this sense, the addition of ODR makes our legal system more robust in its ability to accommodate pro se litigants.

Existing ODR platforms also implicitly provide guidance on the law and litigation process to litigants. For instance, ODR hearings are configured for the litigant and legal issue in question. All content is targeted and laid out in a single dashboard, and material that speaks to irrelevant contingencies can be omitted. Now consider a litigant’s experience walking into a state courthouse, which is, by design or happenstance, an all-purpose space we use to resolve many types of legal matters. A courtroom is not hung with customized signs. The litigant must digest, sort, and navigate. This is costly and often confusing and scary. By contrast, ODR is akin to being met at the door by an usher who helps you to where you need to be, reminds you of your to-dos, and tsk-tsks when you cut a corner or appear distracted. ODR makes the experience less stressful and reduces error. Lawyers also play this role. Thus, even first-gen ODR mitigates the effect of pro se status, but ODR today is better analogized to an usher than to a counselor. A lawyer can help you decide whether going to your seat is a good idea; an usher can just tell you how to get there.

12.2.1 Experience and Predicting Outcomes

One of the most important services a lawyer provides a litigant is an informed, experienced perspective on the likely outcome of a case, with some overall take on whether the outlook is “good.”Footnote ⁴⁴ Typically, during intake, the prospective litigant describes the nature of the dispute, key aspects of the case, and the like, and the lawyer may even offer some preliminary advice. Once retained, however, the lawyer will engage in more intense prediction-oriented activity on behalf of the client, perhaps after researching the law, collecting more information, and weighing the necessary investment, probable venue, expected legal rulings, possible judges, and even likely jurors. These predictions are necessarily fuzzy; there is considerable uncertainty, but as time resolves many contingencies (e.g., the identity of the opposing attorney), predictions will become more accurate. Consequently, the lawyer is likely to revisit the prediction task repeatedly, presumably at each important decision point, when the litigant might seek advice on how to proceed. In a traditional litigation setting, the prediction problem is a complicated one; the environment is relatively unstructured, and the variables are nearly infinite. There are also conflicts of interest and cognitive biases tugging on a lawyer’s predictions.

A lawyer’s ability to “predict” a dispute’s outcome builds on the human equivalent of supervised learning.Footnote ⁴⁵ In most cases, the client defines a “good” outcome for the lawyer.Footnote ⁴⁶ But even if the target is unclear or moving, the client and the lawyer are normally decided on the type of outcome that matters (e.g., damages, liability, share of custody, opportunity to be heard, etc.). The lawyer’s task is to take the client’s account, the law, the client’s set of plausible “moves,” the presiding judge, and anything else observable to the lawyer and then predict an outcome using the agreed-upon metric of success. This prediction may come in the form of an expected outcome alone and possibly with some measure of uncertainty that implicitly conveys the expected accuracy of the prediction (e.g., “I think you’ll get $75K, give or take $10K”). If the client defines a minimally acceptable outcome, the lawyer will review the likely consequences for each set of potential moves and either report that this outcome is unrealistic or that taking a particular set of actions will be necessary (under current circumstances).

How does a lawyer do this? The lawyer effectively cognitively “models” prior cases to understand the complicated relationships between facts, choices, and outcomes. Put another way, lawyers detect patterns between predictors and outcomes.Footnote ⁴⁷ The greater the number and variety of cases and types of predictors that lawyers incorporate into their modeling, the more flexible, unbiased, and accurate their predictions can be. A mental model is what we mean when we talk about the value of experience. An expert lawyer has witnessed many cases with many different characteristics proceed under many different circumstances. Delivering accurate predictions is helpful because they can guide a litigant’s behavior toward their preferred outcome, whatever it happens to be. If the litigant’s goal is to maximize their net “return” from a dispute, a schedule of litigation strategies (including their costs) and their likely outcomes (and uncertainties) produced by a lawyer is what a litigant needs to succeed.

ODR platforms can perform this task. In fact, under the circumstances, they may be able to do a better job.Footnote ⁴⁸ First-gen ODR platforms already access an individual litigant’s case, drawing information from the court’s case management system. Once a case resolves, the platform archives the record and moves onto the next case. But there is no reason an enhanced platform cannot build models from all prior cases and even from data outside the court’s case management system. Models can incorporate any plausible predictor, including judge identity, hearing timing, and docket backlog. By contrast, lawyers build models only from their own cases or those about which they hear or read (inevitably with error and uncertainty), and only with what they can observe about those cases and their circumstances. In effect, an enhanced ODR platform could display a distribution of how similar past cases – or, with enough data, only identical ones – fared using the litigant’s preferred measure of success. These “predictions” (tendered as descriptions of what happened in prior cases – not as promises or legal advice!) can be presented at decision points and can be joined with statistics to impart precision.Footnote ⁴⁹

The challenges to operationalizing these ideas are manageable.Footnote ⁵⁰ In many ways, litigation that occurs in an ODR environment may be more amenable to accurate prediction than litigation in a more traditional environment because the platform can easily capture the information about cases, choices, and outcomes needed for prediction. An ODR system may be more structured and less nuanced, either by necessity or design, which might also simplify the prediction problem. Consider an enhanced platform with asynchronous, text-based communication that requires parties to answer the same questions in the same order with the same answer options as part of an online hearing (versus open court with a judge asking different questions in different ways and expecting a narrative response on the spot) and where the system necessarily prevents or obscures certain actions (e.g., a litigant can’t visibly sigh or roll their eyes at a judge).Footnote ⁵¹ The number of predictors would no longer be infinite because the environment eschews legally irrelevant details; in other words, the medium itself might simplify some of the prediction problems a lawyer would normally face in court.Footnote ⁵²

12.2.2 Navigating, Counseling, and Identifying Options

Lawyers often present options. They take raw facts and abstract law and suggest possible legal solutions. They also identify various strategies (or implement them directly), and they help clients weigh the upsides and downsides of those strategies. Lawyers do not necessarily perform this task well. The quality of counseling, when it occurs, is often suspect. Lawyers implicitly build models, but they also suffer from biases (e.g., availability), have limited observational and processing capacity, and must navigate their own conflicts (like economizing on time and avoiding high-risk innovations). In most contexts, lawyers are also busy. Identifying options, discussing them with clients – these activities take time. Consequently, lawyers work from scripts,Footnote ⁵³ stocked with standard “moves” that usually do the trick in the vast majority of situations. Lawyers may deliver these options in rote fashion, with little thought paid to details that are individually unlikely to make a material difference in the long run (even if, collectively, such details can alter a legal dispute’s trajectory).

This account is designed to present a human lawyer as a fairly simple algorithm. The lawyer asks intake questions, processes the answers, identifies the nature of the dispute and a set of typical solutions, explains the most common approaches to the client, and translates the client’s reaction into a set of choices or next steps. Two tasks are occurring here. One is pattern recognition (the main point here). The second is prediction combined with an interpretation of what the client values. Put differently, lawyers determine the sort of dispute they face, collect relevant information for a dispute involving such features, identify an array of potential approaches or strategies, and assist the client in understanding and deciding between them.

This last step – helping a litigant understand and evaluate various options – falls squarely in the camp of outcome prediction. Enhanced ODR can define a large number of potential outcomes. Not all, true, but easily those outcomes that would matter to 99 percent of litigants. Counseling between options can be carried out simply by informing litigants of the likelihood that certain outcomes will manifest if the litigant pursues, say, track 1 or track 2.

With a real lawyer, counseling involves nuance.Footnote ⁵⁴ But much of that nuance is the lawyer attempting simultaneously to ascertain a client’s preferences. An enhanced ODR platform would do less “screening” and instead make much more information available to the client so they may digest with their own priorities in mind instead of relying on a black-box lawyer. There are challenges here: Litigants also face cognitive limits, and while they may have more time to immerse themselves in their own affairs, too much data can be worse than too little.Footnote ⁵⁵ Just as an intimidating courthouse can paralyze, so too can an environment that dumps unstructured information on litigants and then asks them to sift it.Footnote ⁵⁶ Thus, ODR platform structure and design must not only be accessible but also support effective decision-making.Footnote ⁵⁷ We already use technology to help people make important choices about many things.Footnote ⁵⁸ Even in the legal-aid and access-to-justice contexts, existing decision support tools streamline processes, minimize confusion, and improve decision-making.Footnote ⁵⁹ Efforts are imperfect but improving,Footnote ⁶⁰ and one must remember that the relevant benchmark is a pro se world with no support whatsoever.

To counsel, lawyers categorize a dispute and then compile the information necessary to identify options, avoid legal and factual pitfalls, and assemble plausible strategies (matched with predictions). This is complex, and early versions of enhanced ODR will likely be subject-matter specific. But precedents for algorithmic technology of this sort already exist, and courts should avoid letting the perfect be the enemy of the good. Legal aid groups already deploy triage and intake forms that are “smart.”Footnote ⁶¹ An initial goal for next-gen ODR might be to determine a litigant’s eligibility for digital or other assistance by collecting critical information about the litigant’s situation.Footnote ⁶² The law’s many branches can be incorporated directly into questions put to users.Footnote ⁶³ Structure in the law and implicit groupings of fact patterns will lay bare most likely strategies.

There is no limit to how complex any enhanced ODR data collection process might be. But this is also true when a litigant hires an attorney: The litigant explains their situation, and the attorney asks questions in response. The attorney may also look over papers, review video, or examine other evidence. This exchange might take a while, but lawyers ultimately triage and end their information gathering, and ODR software can too. As natural language processing improves, faster intake methods that ask open-ended questions instead of closed-ended questions can reduce the total number of questions.Footnote ⁶⁴ Analysis of narrative answers can trigger relevant follow-up inquiries.Footnote ⁶⁵ But there are reasons doctors don’t only ask “so, what’s bothering you?” at an appointment. Instead, you are first subjected to a long list of questions designed to prompt you to think about every system and part of your body.Footnote ⁶⁶ Any natural language response to an open-ended question like “what’s your legal problem?” may come from a person unfamiliar with the law whose take on what matters may be off-base.Footnote ⁶⁷ Still, natural language responses, perhaps even voice submissions, might be a better, more accessible option for some litigants.Footnote ⁶⁸

A barrier to making data-collection functionality successful in next-gen ODR platforms is simply how long it might take a litigant to get in the front door. So much of what is good about ODR is that it is easy to use and minimally costly to try. Next-gen ODR might dissuade people from using courts all over again if it bogs down with seemingly countless questions and checklists. But consulting with a lawyer takes no small amount of time, and stacks of forms are not new to human institutions. Nevertheless, enhanced ODR platforms might be more attractive to more people if guidance and counseling functions were designated as optional.

12.2.3 Replication/Obfuscation/Translation versus Representation

Lawyers aren’t just analytical input-output machines offering a litigant legal expertise in the background. Lawyers are corporeal and play a physical role on the stage of our justice system.Footnote ⁶⁹ They actually “do” law by going to a courthouse to serve as their client’s mouthpiece. The corporeal representation function of lawyering matters in at least three ways in the context of court-connected ODR: lawyers replicate a litigant’s ability to be physically present, lawyers obfuscate litigant traits, and lawyers translate and distill a litigant’s lay arguments into an “expert’s” legal arguments. Considering these roles separately demonstrates that enhanced ODR can advance these functions through text on a screen or other digital-information display even without a human body in a courtroom.

First, lawyers allow clients to be in two places at once. This function reduces the cost of litigation to clients, courts, and other parties, since schedule conflicts can slow litigation. Representation offers flexibility to meet competing obligations. Often, a client and their attorney come together in a courtroom at critical junctures, but there are many stages when a lawyer can physically “be” the client for purposes of advancing a case. Technically, ODR is unable to fulfill this function because, whatever it is, software does not stand in for a litigant before other parties or decision-makers. Yet, in an ODR environment, there is arguably no need for such a service in the typical case. Indeed, unlike hearings that take place at a particular time and place, ODR can be more flexible, accessible, and efficient, making the use of a lawyer to “cover” for someone less important.

Second, lawyers can “obfuscate” client traits. When judges walk into a courtroom and see a litigant’s race, gender, age, or other identity traits, evidence suggests that unconscious implicit bias, if not explicit bias, affects subsequent decision-making.Footnote ⁷⁰ Furthermore, the anticipation of such bias can alter a litigant’s ability to communicate well in a courtroom. One strategy for a litigant facing the possibility of discrimination is to hire a lawyer with different – perhaps socially “preferred” – characteristics to block, blunt, or attenuate any such bias. Lawyers even advertise on this basis – for example, hinting at the advantages of a female lawyer defending a male defendant accused of sexually assaulting a female victim.Footnote ⁷¹ True, having a lawyer does not necessarily preclude a judge from ascertaining litigant identity traits, but outside of explicit, intentional discrimination, even sharing the stage with an in-group lawyer may disrupt the psychological processes that lead to bias.

For those unable to reduce their exposure to bias by using a lawyer,Footnote ⁷² ODR offers a substitute, perhaps superior solution. ODR can structure online communication to insulate judges and other decision-makers from legally irrelevant information that might trigger implicit biases (or allow purposeful discrimination). At least some first-gen ODR systems, for example, do not include a litigant’s driver’s license picture in the judge’s dashboard. At least one court collects required picture ID information only after the judge decides the case but before the ruling is entered. First-gen ODR systems, by tracking traditional in-person processes, still tend to make a litigant’s name visible (which may reveal gender and ethnicity) and, in some instances, date of birth (which, with some math, reveals a litigant’s age).Footnote ⁷³ ODR platforms can go further by thoughtfully, comprehensively obscuring litigant traits that are legally irrelevant (or even legally relevant when they are likely to bias or confuse decision-making),Footnote ⁷⁴ whenever it is consistent with fair process.

Third, lawyers provide a “translation” function to clients. Lawyers distill what they learn from clients into core substantive facts, and then assemble and present those facts in the highly reticulated way that legal actors expect from legal professionals.Footnote ⁷⁵ This professional repackaging may augment a litigant’s story and substantive arguments by making them more palatable, reliable, and understandable to a judge.Footnote ⁷⁶ Or it may just be a key into the club. If there are lawyers on both sides, any imprimatur may cancel out, yet the dynamics of the prisoner’s dilemma apply, so all who can “lawyer up” still do so. Pro se litigants are left behind. Even if translation and delivery by an expert improves the litigant’s prospects (relative to a counterparty), it remains an open question whether this function enhances the accuracy or efficiency of any adjudication. Regardless, if only one party has access to an attorney’s stamp of approval or can speak “legalese,” a pro se gap might develop.Footnote ⁷⁷

Enhanced ODR can diminish the role that legalese and professional status might play in litigation by reducing their use, making them ambiguous or less salient, or facilitating a pro se litigant’s ability to employ them within the platform. ODR design can encourage (or require) litigants to use plain language, either via the structure of its data collection strategies (e.g., forms) or through ex post screening of user language. Alternatively, one can imagine a more involved ODR process that educates litigants about the meanings of legal words or legal communication norms or that offers something closer to a translation service, much the way smart form procedures operate today, by giving people choices. Either way, ODR platform “rigidity” in the allowable scope and style of communication can be a disparity-reducing positive;Footnote ⁷⁸ such structure can ensure that parties speak the same language while also giving them equal opportunities to be heard.

Importantly, reducing “degrees of freedom” in ODR communications can also close a back-door source of implicit bias. An ODR system that scrubs case materials of identity-trait data after having encouraged a litigant to submit an open-ended statement may be closing the barn door after the horse has bolted. Intentionally or unintentionally, litigants reveal personal traits in their communications:Footnote ⁷⁹ they explicitly indicate their race, gender, occupation, or age,Footnote ⁸⁰ or they implicitly reveal these traits through language that correlates with demographic characteristics.Footnote ⁸¹ In any event, to the extent that legal representation liberates litigants from the need to speak legalese in the courtroom and insulates litigants from implicit bias by insulating judges from triggering face-to-face interactions, ODR systems have the potential to do much the same through careful design and creative solutions.