If I recall rightly the Pokémon Go locations were derived in part from an earlier (and far better) game called Ingress. Players could submit candidate locations, but it's possible that this was mostly ignored, and/or some form of AI was used to select or filter those candidates. It's also possible that Ingress had a racial bias in its userbase.
>The game creator Niantic Labs revealed that the Pokemon Go map was derived from a previous augmented reality game, Ingress. Ingress crowdsourced its map from users, who tended to be young, male, white, and English-speaking.
Similarly, from the attached article:
>"It turns out Niantic, which makes Pokémon Go, relied on a map from a previous augmented reality game called Ingress, which was crowd-sourced from its mostly male, tech-savvy players," she wrote in a blog post. "The result is a high concentration of PokéStops in commercial and downtown areas of some cities, while there are typically fewer PokéStops in non-white or residential areas, if there are any at all."
It could be there is some other AI-related problem for Pokemon Go hidden in one of the other articles (they all seem to be about unrelated things - one is about Jynx, one is about the experiences of a black person playing the game, another is speculating the Pokemon Go is a CIA operation...), but the incident report itself doesn't make any allegations of an AI-related issue.
I'm still not sure if some of those stories were viral marketing or just a bizarre reflection of our zeitgeist in the black mirror.[0]
[0] - Exampled by: https://www.dailymail.co.uk/news/article-3734361/Woman-tells...
This is also a dubious interpretation because it assumes more people being random visitors to a neighborhood is somehow a benefit. The cynical side of me also says that if the majority of visitors were to non-white neighborhoods that would've also been called a harm.
Even without a neural net based model, it's possible we run into many of these incidents...
> Vanderbilt University's Office of Equity, Diversity and Inclusion used ChatGPT to write an email addressing student body about the 2023 Michigan State University shooting, which was condemned as "impersonal" and "lacking empathy".
The bar is pretty low for what's considered an "incident". Writing a cold email eh?
But in this day and age you just need 4 seconds to look at a page of headlines, numbers, and a conclusion will be drawn.
I'd hardly conclude that email as an "incident". There's incidents every day of people using technology and screwing up - we don't have a "Reply-AllIncidents.com"
I'm all for highlighting and examing real, scary, tangible problems with AI. But it feels like you've got the bar way too low here.
"Harm" is an amalgamous word that not even society knows how to deal with. For instance, we apply harm reduction to some of the most chemically addictive and deadly substances on the planet, yet many of us cannot imagine applying that to things like guns.
This is to say, you've so far created a database of immeasurable things by design, which just makes it a ledger of things you care about. There are meaningful things to measure here though. You could measure outcomes, analogous to E2E tests. Count the number of humans injured, financially penalized, legally penalized, or emotionally damaged. Once you've gathered enough information you can begin to weight them by category and apply a logarithmic scale. This makes results more clear and doesn't bias them in terms of people's perceptions or preferences.
https://incidentdatabase.ai/cite/30/
Because the robots (who almost definitely were using no AI whatsoever) weren't producing quickly enough, workers in a joint Panasonic/Tesla factory had to be shifted from making batteries for Panasonic to making batteries for Tesla.
I am not sure how these workers will ever recover and moreover considering that Tesla and Panasonic lines were plausibly 18650 production it's entirely possible the workers don't even know about this incident. Oh, the humanity.
[0] https://arxiv.org/abs/2211.10384
[1] https://incidentdatabase.ai/editors-guide/
[2] Listed in the report here: https://incidentdatabase.ai/cite/298/#r2471
https://incidentdatabase.ai/cite/24/
> A 22-year-old worker at a Volkswagen plant was "crushed to death" by a robotic arm. The worker was inside the "safety cage", meant to separate humans from the machines, to install a piece of the robot when an arm struck him, pinning him to a metal plate. He was resuscitated, however he died later at the hospital. Volkswagen is citing human error as the cause of the accident.
https://incidentdatabase.ai/cite/30/
> The goal of manufacturing 2,500 Tesla Model 3's per week was falling short by 500 cars/week, and employees had to be "borrowed" from Panasonic in a shared factory to help hand-assemble lithium batteries for Tesla. This output at assembly factories has led CEO/Founder Elon Musk to revisit the management and hiring strategies of the company.
That one also is more like a poor strategic choice/execution than an incident.
>> Alleged: Niantic Labs developed and deployed an AI system, which harmed non-white neighborhoods and communities of color.
> Crowd-sourcing is not "AI".
The offense was the 'AI system' which had a bias for placing those locations in white neighborhoods. The crowdsourced investigation of that offense was not the offense itself...
Consider this incident:
https://incidentdatabase.ai/cite/73/#r1325
>Description: Through a crowdsourcing social media campaign in 2016, several journalists and researchers demonstrated that augmented reality locations in the popular smartphone game Pokemon Go were more likely to be in white neighborhoods.
>Alleged: Niantic Labs developed and deployed an AI system, which harmed non-white neighborhoods and communities of color.
Crowd-sourcing is not "AI". And the linked articles are things like Nintendo redesigning the pokemon Jynx to not look so much like a racial charicature.
It's hard to see the value of this sort of database if the indexed items are so unreliable. How can I trust any conclusions I might draw unless I go through item-by-item to verify them?