Bans on Facial Recognition Are Naive. Hold Law Enforcement Accountable for Its Abuse
Broader police reform may be difficult to achieve. But in the long run, it will be more effective than any specific technology ban.
Jun 17, 2020 The Hill
Don't Make the Pandemic Worse with Poor Data Analysis
The need for immediate answers in the face of severe public health and economic distress may create a temptation to relax statistical standards. But urgency should not preclude expert analysis and honest assessments of uncertainty. Mistaken assumptions could lead to counterproductive actions.
May 6, 2020 The RAND Blog
Did No One Audit the Apple Card Algorithm?
Complex, opaque technologies like artificial intelligence provide significant benefits to society. But those benefits don't eliminate the need for accountability and transparency.
Nov 21, 2019 The RAND Blog
Keeping Artificial Intelligence Accountable to Humans
Artificial intelligence (AI) systems are often only as intelligent and fair as the data used to train them. To enable AI that frees humans from bias instead of reinforcing it, experts and regulators must think more deeply not only about what AI can do, but what it should do—and then teach it how.
Aug 20, 2018 TechCrunch
The Human Side of Artificial Intelligence: Q&A with Osonde Osoba
Osonde Osoba has been exploring AI since age 15. He says it's less about the intelligence and more about being able to capture how humans think. He is developing AI to improve planning and is also studying fairness in algorithmic decisionmaking in insurance pricing and criminal justice.
May 1, 2018
Rethinking Data Privacy
Society benefits from the exchange of large-scale data in many ways. Anonymization is the usual mechanism for addressing the privacy of data subjects. Unfortunately, anonymization is broken.
Oct 5, 2016 Inside Sources