Opacity in AI used to be an academic problem - now it's everyone's problem. In this piece, I define the issues at stake, and how they tie into the ongoing discussion on AI ethics.
I've addressed whether fairness can be measured - but can it be automated? These are central questions as we contend with the real world consequences of algorithmic bias.
By now, most AI practitioners acknowledge the universal prevalence of bias, and the problem of bias in AI modeling. But what about fairness? Can fairness be measured via quantifiable metrics? Some say no - but this is where the debate gets interesting.
Rolls-Royce has created a ‘five checks AI philosophy’ that aims to externally interrogate whether its AI systems are acting fairly.
No, you can't program your AI for empathy or ethics. But you can certainly confront the problem of bias. In part two of revisiting AI ethics, we examine how bias, data management, and privacy should be addressed.
If Pfizer and Moderna executives can use the 10b5-1 rule to advantage without blinking, then what hope for a meaningful ethics discussion in technology?
Executive compensation that's linked to the execution of questionable plans opens questions that strike at the heart of the ehtics debate in technology.
AI ethics are having a hard time keeping up with AI. Academic debates may be interesting, but organizations need a practical AI ethics framework. Where do we go from here?
Algorithmic bias is a thorny topic with lots of examples of bad practice to point to. But what's the long-term solution to a problem that needs to be tacked if AI's potential is to be realized?
AI evangelists pay lip service to solving AI bias - perhaps through better algorithms or other computational means. But is this viable? Is bias in AI inevitable?
Transparency isn't the silver bullet that's going to address every ethical concern around AI deployment, but it's an essential bedrock on which to build.
Explainability has moved from an academic debate to a significant barrier to AI adoption. A slew of new tools and approaches are intended to address this problem - but will they close the explainability gap?
Big tech is playing a growing role in fighting climate change and promoting the use of data to encourage energy efficiency.
Some diverse, exciting technology innovations around drone technology, all of which demand a big dose of common sense from the sector and its regulators.