It was about this time last year that I pitched the team at DATAVERSITY the idea of this monthly column on data ethics. There’s certainly been no shortage of interesting questions to cover and I’ve enjoyed writing about both the practical and more philosophical aspects of this topic. As we wrap up this year and head into a new one, I have some thoughts on this question:
How can you learn more about data and AI ethics?
That’s my segue into telling you about some new courses I’ve launched with DATAVERSITY and to recommend a little holiday reading.
Introducing the Data and AI Ethics Learning Plan
If you’re like me, you’re probably already thinking about professional development opportunities and new skills that you want to tackle in the coming year. I’m thrilled to partner with DATAVERSITY to offer three new courses that form a learning plan in data and AI ethics. One of my goals is to educate more people about data and AI ethics so that we can see this work woven into data and AI governance agendas. If you enjoy this column, I think you’ll enjoy these courses.
Holiday Reading Recommendations
There are so many fantastic books available on data, AI ethics, and related topics. Here are a few of the works that have been key to my learning. Some are classics, others are newer works, some are more academically focused while others are more widely accessible. All provide valuable insights that I think you’ll find useful to better understand the ways in which data is used in AI systems and the ensuing impacts on our world.
Algorithms of Oppression by Safiya Umoja Noble – “a classic in the field that helped set me on my current career path”
Atlas of AI by Kate Crawford – “unpacks the materiality of data and AI systems”
Cloud Ethics by Louise Amoore – “explores how our ethics are entangled with the algorithmic”
Data Conscience by Brandeis Hill Marshall – “wonderful mix of technical instruction with practical ethical guidance”
Discriminating Data By Wendy Hui Kyong Chun – “beautifully illustrates how discrimination is encoded in data and networks’’
How We Became Our Data by Colin Koopman – “from birth certificates to our digital platforms – we’re all informational people” (more in-depth review on my blog)
Justice by Michael Sandel – “not a data or AI book – but a deep unpacking of issues around justice that are necessary for ethical deliberation”
The Age of Surveillance Capitalism by Shoshana Zuboff – “a book I return to often, centered on the economic and socio-political aspects of data and algorithms”
The AI Mirror by Shannon Vallor – “a much better metaphor for AI and a call to action to embrace our humanity”
The Data Revolution by Rob Kitchin – “classic primer for critically understanding how data is constructed”
If you have reading suggestions for me, send me a note. I plan to continue this column in the new year and look forward to addressing more challenging data and AI questions. Until then, all the best for you and yours this holiday season.
Send Me Your Questions!
I would love to hear about your data dilemmas or AI ethics questions and quandaries. You can send me a note at hello@ethicallyalignedai.com or connect with me on LinkedIn. I will keep all inquiries confidential and remove any potentially sensitive information – so please feel free to keep things high level and anonymous as well.
This column is not legal advice. The information provided is strictly for educational purposes. AI and data regulation is an evolving area and anyone with specific questions should seek advice from a legal professional.