fast.ai has just released a free, online course on Applied Data Ethics, which contains essential knowledge for anyone working in data science or impacted by technology. The course focus is on topics that are both urgent and practical, causing real harm right now. In keeping with the fast.ai teaching philosophy, we will begin with two active, real-world areas … [Read more...] about The Essential Data Ethics Course For Everyone Working In Tech
Ethics & Safety
Being good is easy, what is difficult is being just. ― Victor HugoWe need to defend the interests of those whom we’ve never met and never will. ― Jeffrey D. SachsNote: This article is intended for a general audience to try and elucidate the complicated nature of unfairness in machine learning algorithms. As such, I have tried to explain concepts in an accessible way … [Read more...] about Programming Fairness in Algorithms
If you can’t explain it simply, you don’t understand it well enough. — Albert EinsteinDisclaimer: This article draws and expands upon material from (1) Christoph Molnar’s excellent book on Interpretable Machine Learning which I definitely recommend to the curious reader, (2) a deep learning visualization workshop from Harvard ComputeFest 2020, as … [Read more...] about Guide to Interpretable Machine Learning
As the importance of ethical considerations in AI applications is being recognized not only by ethicists and researchers but also by industry tech leaders, AI ethics research is moving from general definitions of fairness and bias to more in-depth analysis. The research papers introduced in 2019 define comprehensive terminology for communicating about ML fairness, go from … [Read more...] about Top 12 AI Ethics Research Papers Introduced In 2019
AI bias doesn’t come from AI algorithms, it comes from people. What does that mean and what can we do about it?Technology is not free of humansNo technology is free of its creators. Despite our fondest sci-fi wishes, there’s no such thing as ML/AI systems that are truly separate and autonomous… because they start with us.All technology is an echo of the wishes of … [Read more...] about Pay Attention to That Man Behind the Curtain
How will you prevent embarrassment in machine learning? The answer is… partially.Expect the unexpected!Wise product managers and designers might save your skin by seeing some issues coming a mile off and helping you cook a preventative fix into your production code. Unfortunately, AI systems are complex and your team usually won’t think of everything.There will be … [Read more...] about How to Prevent Embarrassment in AI
I want to talk about technical approaches to mitigating algorithmic bias.It’s 2019, and the majority of the ML community is finally publicly acknowledging the prevalence and consequences of bias in ML models. For years, dozens of reports by organizations such as ProPublica and the New York Times have been exposing the scale of algorithmic discrimination in criminal risk … [Read more...] about Algorithmic Solutions to Algorithmic Bias: A Technical Guide
The “AI for Social Good” umbrella“AI for social good”. We increasingly see related initiatives by organisations like Google and Microsoft, conferences, reports and workshops in major “AI” conferences like Neurips, ICRL, and ICML. However, AI for good has become an arbitrary term.Not only AI is a conflated term (for which we can write books about) but … [Read more...] about What Is This “AI For Social Good”?
Many people incorrectly assume that AI is only for an elite few– a handful of Silicon Valley computer science prodigies with monthly budgets larger than most people’s lifetime earnings, turning out abstruse academic papers. This couldn’t be more wrong. Deep learning (a powerful type of AI) can, and is, being used by people with varied backgrounds all over the world. A small … [Read more...] about Dairy farming, solar panels, and diagnosing Parkinson’s disease: what can you do with deep learning?
AI is being increasingly used to make important decisions. Many AI experts (including Jeff Dean, head of AI at Google, and Andrew Ng, founder of Coursera and deeplearning.ai) say that warnings about sentient robots are overblown, but other harms are not getting enough attention. I agree. I am an AI researcher, and I’m worried about some of the societal … [Read more...] about Five Things That Should Scare You About AI