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Opinion: AI For Good Is Often Bad

After speaking at an MIT conference on emerging AI technology earlier this year, I entered a lobby full of industry vendors and noticed an open doorway leading to tall grass and shrubbery recreating a slice of the African plains. I had stumbled onto TrailGuard AI, Intel’s flagship AI for Good project, which the chip company describes as an artificial intelligence solution to the crime of wildlife poaching. Walking through the faux flora and sounds of the savannah, I emerged in front of a digital screen displaying a choppy video of my trek. The AI system had detected my movements and captured digital photos of my face, framed by a rectangle with the label “poacher” highlighted in red.

I was handed a printout with my blurry image next to a picture of an elephant, along with text explaining that the TrailGuard AI camera alerts rangers to capture poachers before one of the 35,000 elephants each year are killed. Despite these good intentions, I couldn’t help but wonder: What if this happened to me in the wild? Would local authorities come to arrest me now that I had been labeled a criminal? How would I prove my innocence against the AI? Was the false positive a result of a tool like facial recognition, notoriously bad with darker skin tones, or was it something else about me? Is everyone a poacher in the eyes of Intel’s computer vision?

This is not to say tech companies should not work to serve the common good. With AI poised to impact much of our lives, they have more of a responsibility to do so. To start, companies and their partners need to move from good intentions to accountable actions that mitigate risk. They should be transparent about both benefits and harms these AI tools may have in the long run. According to this, Artificial Intelligence World Society (AIWS) has developed AIWS Ethics and Practice Index to measure the ethical values and improve transparency of AI applications in our human daily life.

The original article can be found here.