Book contents
- Data Science in Context
- Reviews
- Data Science in Context
- Copyright page
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Introduction
- Part I Data Science
- Part II Applying Data Science
- Part III Challenges in Applying Data Science
- Part IV Addressing Concerns
- Chapter 15 Societal Concerns
- Chapter 16 Education and Intelligent Discourse
- Chapter 17 Regulation
- Chapter 18 Research and Development
- Chapter 19 Quality and Ethical Governance
- Recap of Part IV: Addressing Concerns
- Chapter 20 Concluding Thoughts
- Appendix Summary of Recommendations from Part IV
- About the Authors
- References
- Index
Chapter 16 - Education and Intelligent Discourse
from Part IV - Addressing Concerns
Published online by Cambridge University Press: 29 September 2022
- Data Science in Context
- Reviews
- Data Science in Context
- Copyright page
- Contents
- Figures
- Tables
- Preface
- Acknowledgments
- Introduction
- Part I Data Science
- Part II Applying Data Science
- Part III Challenges in Applying Data Science
- Part IV Addressing Concerns
- Chapter 15 Societal Concerns
- Chapter 16 Education and Intelligent Discourse
- Chapter 17 Regulation
- Chapter 18 Research and Development
- Chapter 19 Quality and Ethical Governance
- Recap of Part IV: Addressing Concerns
- Chapter 20 Concluding Thoughts
- Appendix Summary of Recommendations from Part IV
- About the Authors
- References
- Index
Summary
This chapter discusses the importance of education and rigor in the definition and use of vocabulary surrounding automation and data. More education helps individuals by enhancing their ability to understand data and data science’s growing impact, and to both contribute to and benefit from the field. A more knowledgeable public and a clear vocabulary for discourse is needed to have better communication and debate.
- Type
- Chapter
- Information
- Data Science in ContextFoundations, Challenges, Opportunities, pp. 237 - 243Publisher: Cambridge University PressPrint publication year: 2022