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> At artificial-intelligence conferences, researchers are increasingly alarmed by what they see. This is because there is an increasing proportion of people th
by iujjkfjdkkdkf 6y ago
> At artificial-intelligence conferences, researchers are increasingly alarmed by what they see.
This is because there is an increasing proportion of people that is not going to the conferences for the science and instead to try to hijack the conferences with their own agenda. It's of course their right to make a fuss, but it would be nice to still have venues that are focused on the science and not the other political stuff.
- Nalta 6y ago(Citation Needed)
- timkam 6y agoI really don't get it. Nobody at an AI conference is alarmed at what they see in terms of AI research progress. Most well-educated people are alarmed about societal issues that _are also relevant to the application of automated decision-making and machine learning_. It's an applied research opportunity to investigate the issues (and as such, it is hyped because it is easy to "sell" to get funding); but it's not that AI research brings "bias" that didn't exist in society before. It's the same as for a rule-based system, or let's say, even a programming language: for sure, it can automate and hence exacerbate "unfair" decisions, but the problem is not in the specification, but in the specifying person/human. However, having a clear specification makes it easier to test/audit/verify and hence we (as a society) should do so. We don't need to burn down academic prototypes just because they make some naive assumptions about the application domain, though.
- loopz 6y agoThe whole point is that biases are inherent in most models, no matter who the builders are.
- Guest42 6y agoWhat types of models and what types of bias are you referring to?
- deleted 6y ago[deleted]
- slg 6y agoAny model created using biased data will inherently mirror that bias unless there are active steps made to counteract this effect. For example, basically any financial evaluations of US citizens will likely result in an inherent bias against Black people due to institutional biases such as redlining that have long lasting socioeconomic and demographic repercussions. This might mean that something as simple as incorporating the zip code of a home into a mortgage pricing AI can end up with a racial bias.
- Guest42 6y agoI agree that the data will shift the results of the model and that some predictors can be proxies for others that are protected, but the claim was that the models themselves were biased (rather globally) and was curious whether that was shown and if so how.
- slg 6y agoI'm not OP, but I don't think the claim was specifically that models themselves are biased. It is that models are inherently biased because the data they are based on is biased. That might sound the same, but there is a nuanced difference. If you are able to strip the bias from the data, the models will work fine. The problem is the data and not the models.
- refenestrator 6y agoAt what point does this stop being AI's fault and start being an accurate observation of things that are society's fault? Let's say you have a racially-neutral observation of lower income, maybe disability status or a criminal rap in the past. That looks like a bad bet for a loan regardless of color, it just so happens that our society's created a statistical imbalance in those metrics.
- dvt 6y agoThis kind of statement, by its very nature, is vacuous and means nothing (and is most likely made by a non-expert). But on the surface of it seems deep and insightful. Note that it uses weasel words like "biases" and "models" which can actually mean a zillion things.
- loopz 6y agoIt means exactly what it means. No more, no less. sig above got it, so it's not impossible to imagine. No need to be an expert, that shouldn't be necessary. Sorry if I used difficult words. The point is to think it through for yourself anyways, and not depend blindly on authority.
- optimalsolver 6y agoFunny how no one minded when the highly politically-motivated billionaire Peter Thiel was (and still is) pouring enormous amounts of money into AI. I'm more concerned about billionaires with an agenda than no-name researchers giving a talk on cyber-intersectionality.
- timkam 6y agoI think this topic is more about what should be the focus of discussion in the AI community. A key question is: to what extent do AI researchers need to consider ethics and how do they need to consider it? These are hard questions. People in the broader AI community are typically no ethics experts, so the discussions can easily become uninformed and unpleasant, and some people on the extremes of both sides will try to use it to strengthen their profile (or perhaps, some of them simply can't hold their horses). Funding sources are a different topic, and many funding providers fund both AI intersectionality and research towards more effective autonomous weapons systems...
- logicslave 6y agoA good way to gain notoriety and press coverage is to demonize machine learning. Its a bad feedback loop caused by clickbait
- naebother 6y agoI know right, can't even discuss how best to enrich uranium these days without it being made all political or getting assassinated.
- eeZah7Ux 6y agoYou are trying to re-frame ethics as "agenda" and "political stuff." Enough said.
- r7f7rhr 6y agoEthics is the shield of idiots and churches.