Book contents
- Frontmatter
- Contents
- List of figures
- Preface
- Acknowledgements
- About the authors
- Glossary of Technical Terms
- 1 The Accidental Entrepreneur
- 2 A Reflection on the First 300 days
- 3 Why does any Organisation need a Chief Data Officer?
- 4 The Secret Ingredients of a Chief Data Officer
- 5 The First 100 Days
- 6 Delivering a Data Strategy in the Cauldron of BAU
- 7 Avoiding the Hype Cycle
- 8 Relating to the rest of the Business, Especially the C-Suite
- 9 The Chief Data Officer as a Disruptor
- 10 Building the Chief Data Officer Team
- 11 The next 300 Days
- 12 The Different Generations of Chief Data Officers
- 13 What type of Chief Data Officer are you?
- 14 How to Present Yourself as a Chief Data Officer
- 15 The Chief Data Officer and the Technology
- 16 The Hoarding Mentality and how to Break it
- 17 Data and Information Ethics
- 18 The Chief Data Officer and Data Governance
- 19 The Data Revolution
- 20 Advice to Business owners, CEOs and the Board
- 21 Conclusion
- Index
17 - Data and Information Ethics
Published online by Cambridge University Press: 18 February 2021
- Frontmatter
- Contents
- List of figures
- Preface
- Acknowledgements
- About the authors
- Glossary of Technical Terms
- 1 The Accidental Entrepreneur
- 2 A Reflection on the First 300 days
- 3 Why does any Organisation need a Chief Data Officer?
- 4 The Secret Ingredients of a Chief Data Officer
- 5 The First 100 Days
- 6 Delivering a Data Strategy in the Cauldron of BAU
- 7 Avoiding the Hype Cycle
- 8 Relating to the rest of the Business, Especially the C-Suite
- 9 The Chief Data Officer as a Disruptor
- 10 Building the Chief Data Officer Team
- 11 The next 300 Days
- 12 The Different Generations of Chief Data Officers
- 13 What type of Chief Data Officer are you?
- 14 How to Present Yourself as a Chief Data Officer
- 15 The Chief Data Officer and the Technology
- 16 The Hoarding Mentality and how to Break it
- 17 Data and Information Ethics
- 18 The Chief Data Officer and Data Governance
- 19 The Data Revolution
- 20 Advice to Business owners, CEOs and the Board
- 21 Conclusion
- Index
Summary
Introduction
This chapter stresses the importance of ‘making sure you think before you do’. Data is dangerous, it is combustible and should be handled with caution. The theory of unintended consequences is also explored.
The need for customer data ethics arises from two factors – concentrated market power of a few digital tech giants controlling massive amounts of customer data and consumers’ deep seated concerns about how their data is collected and used.
(Mike McGuire, Vice President Analyst in Gartner's marketing practice)Opportunities and ethics
There's a common saying in the UK along the lines of ‘just because you can doesn't mean you should’, usually said to someone who is using their money, skills or power in a way that isn't morally the best. Pulling our company's data together, governing it and making it trustworthy and then capitalising on it for the good of our organisation could give us a tremendous amount of power – so how do we intend to use it? Irrespective of how ethical our intentions are, what about the unintended consequences?
Advances in data and how we use it can and have provided us with huge opportunities to improve our public and private lives. This, coupled with the gradual reduction in human oversight and the growing awareness among the public about the use of data in their everyday lives means these opportunities come at a price: the increasingly significant ethical challenges we face in this area. It's important to find the balance between allowing and even encouraging innovation and facing some really regrettable consequences. We need to be able to build on data, share and collaborate, but to do so in an ethical and sustainable fashion.
Regulation and legislation has also become much more aware of the consequences of the misuse of data; and legal measures around data protection, intellectual property, data storage, anti-discrimination and confidential information all strive to tackle areas where data meets ethical concerns.
A definition of data ethics was formulated by Luciano Floridi and Maricrosaria Toddeo for the Royal Society in late 2016:
the branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithm (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values).
- Type
- Chapter
- Information
- The Chief Data Officer's Playbook , pp. 161 - 168Publisher: FacetPrint publication year: 2020