The latest in AI Ethics consists of AI bias bounty hunting, though this raises a lot of questions, including as considered for aiming at AI-based self-driving cars.
Into the potential “gap” of how to find those insidious AI biases come the heroic and dashing AI biases bounty hunters.
In more modern times, you might be aware that in the 1980s there were some notable bounties offered to find computer bugs or errors in off-the-shelf software packages and then in the 1990’s Netscape markedly offered a bounty for finding bugs in their web browser . Google and Facebook had each opted toward bounty hunting for bugs starting in 2010 and 2013 years, respectively. A few years later, in 2016 even the U.S.
Second, you don’t know for sure what those bounty hunters might do. They could opt to tell the whole world that they found biases in your AI. One supposes this might forfeit getting the bounty, though some might relish the attention or aim to bolster their status for getting consulting gigs and other revenue-generating possibilities. It could perhaps be entirely altruistic. It might be a form of AI activism. I can keep going.
I realize that some of you might be saying that nobody should be releasing AI that has any biases in it. That would seem to solve this whole dilemma about whether to use AI biases bounty hunters or not. Just don’t get yourself into a bounty situation. Make sure your AI developers do the right thing and do not allow AI biases into their AI systems. Perhaps use consultants to do a double-check.
The same could be said in the use case of AI biases. If you offer a sufficient bounty, hopefully, the bounty hunters will bring the discovery of AI biases to your attention. You can then cope with the AI biases in a relatively quiet and measured way. This might forestall a much larger and more daunting problem later on, namely that somebody else finds AI biases in your AI and screams about it to the high heavens.
I might add that establishing a bounty hunting endeavor for AI biases of your AI is a much taller order than you might assume at an initial glance. You will need to scrutinize the bounty hunter submissions. There will be a lot of “noise” in the reported claims, in the sense that many of the claimed AI biases do not exist, though the bounty hunter insists that they found some. Imagine how much labor your own AI teams will be required to examine the bounty claims, explore the validity of each, and then potentially go back and forth with the bounty hunter about whether gold was discovered or not.
The point is that to set up the AI biases bounty effort you would be wise to try and clarify what you consider AI biases to consist of. This requires a Goldilocks kind of calibration. You don’t want to be so confining that the bounty hunters overlook AI biases merely because they don’t fit within your stipulated definition, and nor do you want them to yell “Eureka!” at every morsel of an AI bias that they perchance find.
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