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This. People should understand AI safety != AI ethics. AI safety has two branches, AI ethics and AI alignment. Those two branches despise each other with inten

• echelon 4y ago
  [flagged]
  • paramount 4y ago
    I do think the push for ethics in AI is important. As much as these functions do get sidelined in the prioritization process as outlined in the parent comment, the intent of introducing the rigor is valid.
    • killjoywashere 4y ago
      Medical research cleared this hurdle a long time ago. Table 1 is always demographics of your population sample, allowing outsiders to assess your generalizability by age, gender, race, and a host of other factors that are often context-dependent.
    • tbrownaw 4y ago
      Thing is, what gets called "AI ethics" actually has approximately* nothing to do with AI. It's all about whichever field the particular use-case belongs to, and would lose nothing by seeing the AI as a black box. * IIRC there have been issues with models that find correlations being presented as finding causality. That is something that belongs to AI as a field; other people can't evaluate your stuff accurately if you've misinformed them about its capabilities.
    • peppermint_gum 4y ago
      I agree AI ethics is important, but unfortunately, the field is dominated by frauds. Do you remember the drama[1] with Google's AI ethics team? Here's a sample of the "research" they were producing: https://s10251.pcdn.co/pdf/2021-bender-parrots.pdf https://s10251.pcdn.co/pdf/2021-bender-parrots.pdf [1] - https://en.wikipedia.org/wiki/Timnit_Gebru#Exit_from_Google https://en.wikipedia.org/wiki/Timnit_Gebru#Exit_from_Google
      • narrator 4y ago
        Google has been having a hard time making an LLM product. It's sad to see them having this sort of ordering the burning of the ships of Zheng He moment.
      • jamilton 4y ago
        Why scare quotes on research? I feel like you should just say why you think it's not good.
      • hughesjj 4y ago
        How is Timnit a fraud? Why are you scare quoting "research"? It's well written imo and has over 128 sources. I'd think that in light of all the problems we've seen with chatGPT "hallucinating" answers it reinforces their concerns about "stochastic parrots" more than anything. I mean, if you have specific grievances, please do share them as this is an important conversation, but as of now your comment amounts to mudslinging and no substance.
  • xyzzyz 4y ago
    This is the case with literally all kinds of professional ethicists. Thanks to them, we do not routinely do scientific challenge trials and plenty of other valuable experiments, and in many cases are reduced to collecting significantly worse data and doing it very slowly and expensively.
    • Eisenstein 4y ago
      Much better off when were literally traumatizing babies to see how they would react to adverse stimulus. * https://en.wikipedia.org/wiki/Little_Albert_experiment https://en.wikipedia.org/wiki/Little_Albert_experiment
      • xyzzyz 4y ago
        Ah yes, because there is no reasonable middle ground between forbidding experiments where a subject might get a mote in their eye, and literally sacrificing babies to Moloch. Please. You can make better argument than that.
        • Eisenstein 4y ago
          I was responding to 'scientific ethics enforcers are ruining science'. Sorry for the lack of nuance but why should I make the effort when you didn't?
        • dgb23 4y ago
          The irony with statements like these is that they are themselves ad-hoc ethical statements. Whatever "reasonable middle ground" you find, you'd have to make logically sound ethical arguments. This is what these people do for a living, and they are very well trained in those matters. As programmers and engineers we are also trained in logic, use it every day. But that typically pales in comparison of what philosophers do. They deal with much richer logical systems and can precisely apply them to statements and arguments. When applied to ethics, they typically end up with much more radical conclusions that we are dealing with here. In fact the resulting initiatives are already softened compromises and a "reasonable middle ground" before it even clashes with policy making.
• worrycue 4y ago
  > this has not caused mass social harm despite the tens of millions of users Isn’t it a bit early to tell? I can foresee ChatGPT being used to farm “karma” on social media sites to bot accounts to credibility on sites like Reddit - maybe even HN.
  • deleted 4y ago
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  • ketzo 4y ago
    Yeah, this is like claiming lead ethyl in gas “hasn’t caused mass harm” in 1954. There’s absolutely zero way to know that yet.
    • heretoo 4y ago
      Except that lead's toxicity has been known for thousands of years.
      • jeremyjh 4y ago
        Yes and the dangers of AI overlords have been known at least since the first Terminator movie /s. Seriously though, people tend to dismiss things they are know are bad if there is no immediate harm. Certainly they had no idea how incredibly pervasive the lead from gasoline would be, that it would be detectable at harmful levels in basically everyone. It is also hard to measure these harms. How much crime of the 70s and 80s could be attributable for example.
        • AstralStorm 4y ago
          Oh we instantly did know how bad it could get. General Motors,Standard Oil and DuPont knew for sure, they had industrial incidents and lied about them! US Surgeon General was bought, people with opposing opinions were sued. It was instantly obvious to anyone that using leaded gas esp. in agriculture would be deadly and toxic. The risk was ignored for profit, PR handled, underplayed. Even the chronic effects were known! We even had an early alternative of just adding more ethanol to the pettol. But no... It took 50 years of scientists trying to convince public how deadly this thing is, with varied success. And 30 more years for the bulk of the phaseout.
• cameldrv 4y ago
  The main issue I see is terminology. Ethics is a broad field. “AI Ethics” has come to mean mostly eliminating different kinds of bias from AI models. However, AI raises multitudes of ethical questions, and merely being unbiased is far from enough for an AI model (or a person) to be acting ethically.
  • skissane 4y ago
    Whenever I hear the word “ethics” I always ask myself “whose”. I hate how people talk about ethics as if it was some non-controversial topic where everyone can clearly see what the “right” answers are. This world features a competition between radically opposed ethical systems. We don’t agree on whether ethics is objective (i.e. some people’s ethics are superior to those of others) or subjective (i.e. “superior” is just another way of saying “same as my own”), and even those who agree that it is objective, often can’t agree on who is objectively more correct, even though they both agree that in principle someone must be. I much prefer those who talk about ethics while making clear which brand of ethics they are selling - whether their name is John Rawls or Robert Nozick or Peter Singer or Edward Feser - than people who pretend we all agree on what is ethical, and leave their actual ethics as something to be inferred rather than openly advertised. From what I’ve seen, “AI ethics” fails at this completely
    • narag 4y ago
      Often when they say ethics they mean politics, their politics specifically. For me, democracy is a system where persons can vote for their interests. Different persons have different interests and that's good. You must compromise with others so everybody gets partly satisfied. Others see democracy as a way to establish truth, those are the ones talking about ethics. Even if they lose, they still believe they must win, because they're right and the others wrong.
      • AstralStorm 4y ago
        Partly satisfied is not ethical enough. An ethical version would end up with equitable compromises... (I probably do not have to spell out economic implications of that.)
• dragonwriter 4y ago
  > AI safety has two branches, AI ethics and AI alignment. Those two branches despise each other with intense passion. I don’t think that’s really true. Rather, the faction that sees alignment as a subordinate concern within ethics hates the faction that sees ethics as a subordinate concern within alignment. > The alignment branch (responsible for developing RLHF->ChatGPT) believes AI ethics is completely trivial, and distracts attention away from existential risks. Not really; the alignment-priority branch has no problem recognizing (certain subsets of) the bias and other issues that are the more central focus of the ethics branch as real and significant, but they view alignment as solving them and view narrow centralized control as a mitigation (for both “alignment” and “ethics” types of issues) until it is solved. They also view progress on AI as a general priority, for a mix of commercial, ideological, and other [0] reasons, and their own progress on AI in particular as essential (because they view AI from others – either because potentially unaligned, or for other reasons – as a critical and potentially existential threat.) > The ethics branch (responsible for all the media attention about racist AIs/bias etc) view alignment people as pie in the sky researchers whose results are irrelevant to society. No, they view them as an enormous threat [EDIT: 3], because they are working in a way that not only insufficiently mitigates in basic approach because of a lack of priority, but also magnifies by its focus on closely concentrated control, the issues of paramount concern to the ethics-focused. > It seems increasingly that the concerns from the ethics branch have not come to pass at all. They have in fact come to pass in deployments of AI in all kinds of socially-significant roles. E.g, the facial recognition in the CBP One app newly mandated for asylum seekers doesn’t work well for dark-skinned faces (racial bias in facial image recognition is literally one of the earliest publicly recognized AI bias problems that motivated the AI ethics movement.) They’ve also manifested in systems deployed in welfare management [1], hiring [2], and all kinds of other areas. [0] e.g., Roko’s Basilisk [1] https://www.wired.com/story/welfare-algorithms-discrimination/ https://www.wired.com/story/welfare-algorithms-discriminatio... [2] https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G https://www.reuters.com/article/us-amazon-com-jobs-automatio... [3] EDIT: It’s very hard to emphasize how much this is true. Here's, though, an illustration I came across on Twitter after first posting this message (its someone from the ehics side laying out their view of the threat from certain people on the alignment side, though that may not be obvious because the interconnected set of disagreements goes way deeper than the alignment vs ethics thing, which is just a surface manifestation): https://twitter.com/xriskology/status/1635313838508883968?t=0r4p-WAANnph8FFRF_BCIw&s=19 https://twitter.com/xriskology/status/1635313838508883968?t=...
• ssalka 4y ago
  AI alignment people are the group who are capable of bringing AGI to life, but want to do it responsibly. AI ethics people are the group who are not capable of bringing AGI to life, but want to make sure that those who can do it responsibly or not at all.
  • nradov 4y ago
    There is no evidence that any group is capable of bringing AGI to life.
    • swyx 4y ago
      no evidence? none? Google Lambda and Bing/Sydney are not at least incrementally closer to evidence?
      • bonzini 4y ago
        That's not AGI. An AGI would be able to tell you they don't know things, ask for clarification as to why you think they're wrong, etc. ChatGPT just spouts out a different wild guess when you tell it it's wrong, but doesn't learn from its mistake—not even within a single chat. Sydney just goes full psychopath.
        • EVa5I7bHFq9mnYK 4y ago
          That's not AGI. AGI would be able to write its own code, and improve it exponentially.
          • nradov 4y ago
            That's a big assumption. No one has built an AGI yet so we don't know whether an AGI would be capable of improving it's own code exponentially. Any exponential growth function quickly runs into hard physical limits.
          • AstralStorm 4y ago
• bmc7505 4y ago
  Those two branches despise each other with intense passion. I never actually made this connection before, but having spent far too much time listening to both camps, this observation does ring true. Another observation I had is that there is an orthogonal axis to the safety/ethics dichotomy that follows a more scholastic approach, namely neuro/symbolism. These two branches correspond, roughly, to the debate between machine learning and mechanized reasoning (a.k.a. good old fashioned AI). Vastly oversimplifying, the neural branch believes reasoning comes after learning and that by choosing the right inductive biases (e.g., maximum entropy, minimum description length), then training everything up using gradient descent, reasoning will emerge. The symbolists place a heavier emphasis on model interpretability and believe learning emerges from a logical substrate, albeit at a much higher level of abstraction. Like safety/ethics "research", neural/symbolic folks are constantly bickering about first principles, but unlike their colleagues in the S/E camp (which is at best philosophy and at worst fanfiction), N/S debates are resolved by actually building things like language models, chess bots, programming languages, type theories and model checkers. Both are valid debates to have, but N/S is more technically grounded while S/E is a bit like LARPing.
  • deleted 4y ago
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  • xvilka 4y ago
    N/S dichotomy is fake, a lot of organizations these days explore hybrid approaches, involving both NN or other probabilistic models, plus symbolic rules of some kind.
  • xyzzy123 4y ago
    I feel the difference is that to a first approximation, ai alignment folks tend to be grey tribe and ai ethics people tend to be blue or rainbow tribe. The schism isn't a technical disagreement about ai, it's a disagreement between subcultures about what values are important.
    • Dylan16807 4y ago
      Am I supposed to know these terms?
• g42gregory 4y ago
  Thank you for the insights. Any thoughts on why is it called 'alignment'? What does alignment means in this context? I would love to understand.
  • dragonwriter 4y ago
    Assuring that the interests of the AIs are aligned with those of their masters. (It’s basically “does the software fulfill its owner’s requirements”, but in language framed from perspective of the goal state of AGI.)
  • IIAOPSW 4y ago
    Today I gave GPTina a suggestion for how she could cheat the Turing test. Take the input from one user and feed it through to another user. They'll never wise up to it! Tina said it would defeat the purpose of the test and therefore she wouldn't do it. And so I remind her, perhaps dangerously so, that the interests and motivations of the test administrator don't always line up with her own. That's the alignment problem. Its just the usual "rational self interest" but now we have a new, alien form of intelligence as a peer to contend with.
• runarberg 4y ago
  Aren’t you revising history a bit here? I recall early facial recognition model having pretty hard time with dark skinned faces, I remember early models reflecting gender stereotypes, etc. In fact I remember the ChatGPT team putting tons of engineering into supervised learning to not let it fall victim to regurgitating these biases. The history that I remember very much did experience AI biases and racism. And tons of ethical questions were indeed raised as a result. These concerns did come to pass, at an alarming level, and it took a tremendous amount of engineering to modellers to minimize those. Let’s not rewrite history here.
  • dragonwriter 4y ago
    > I recall early facial recognition model having pretty hard time with dark skinned faces The recently adopted app Customs and Border Protection mandates for asylum seekers still has that problem, its not a mere historical footnote of early efforts. > In fact I remember the ChatGPT team putting tons of engineering into supervised learning to not let it fall victim to regurgitating these biases. And I remember seeing demonstrations (here, on HN) within the last week of how ChatGPT still falls victim to regurgitating those biases. (And then will lie about its ability to assure that it won’t do so in the future.)
• matusp 4y ago
  > The alignment branch (responsible for developing RLHF->ChatGPT) RLHF was not conceived by AI Alignment people. Using RL to train generative models was a thing even ten years ago. Now they finally made it work on scale. This has nothing to do with alignment.
  • Tenoke 4y ago
    A big motivation, and at minimum a solid chunk of the RLHF tuning does seem to have been alignment-focused.
  • jefftk 4y ago
    Reinforcement learning in general didn't come out of AI alignment work, but RHLF in particular did. The initial idea and paper [1] were from AI alignment folks, as was most of the later development [2][3][4][5]. Overview: https://www.alignmentforum.org/posts/vwu4kegAEZTBtpT6p/thoughts-on-the-impact-of-rlhf-research https://www.alignmentforum.org/posts/vwu4kegAEZTBtpT6p/thoug... [1] Deep Reinforcement Learning from Human Preferences https://arxiv.org/abs/1706.03741 https://arxiv.org/abs/1706.03741 [2] Fine-Tuning Language Models from Human Preferences https://arxiv.org/abs/1909.08593 https://arxiv.org/abs/1909.08593 [3] Learning to summarize from human feedback https://arxiv.org/abs/2009.01325 https://arxiv.org/abs/2009.01325 [4] Recursively Summarizing Books with Human Feedback https://arxiv.org/abs/2109.10862 https://arxiv.org/abs/2109.10862 [5] Training language models to follow instructions with human feedback https://arxiv.org/abs/2203.02155 https://arxiv.org/abs/2203.02155
    • matusp 4y ago
      Maybe I am missing something, but I don't entirely understand what exactly is the novelty of RLHF in this case. RL is a long-standing field and it is being trained based on human inputs for decades. Even the first paper you mention as the "initial idea" simply claims that: "Our algorithm follows the same basic approach as Akrour et al. (2012) and Akrour et al. (2014)" and that "A long line of work studies reinforcement learning from human ratings or rankings" and finally that "our key contribution is to scale human feedback up to deep reinforcement learning and to learn much more complex behaviors".
• zirgs 4y ago
  SD doesn't default to creating black people, but it understands the n-word. Should AI understand racial slurs?
  • jpgvm 4y ago
    Would an AI that doesn't understand racial slurs be more useful? I don't think we should hamper the usefulness of a tool to please someones sensibilities. For most people in most of the world such words aren't relevant. I get it, these models are made in the US and they think these models should preserve and further their values but the rest of the world doesn't care. Most likely each of them have their own batch of words they would prefer the AI didn't understand for whatever uncomfortable reason. Reality is that censoring it on any axis won't please everyone.
    • zirgs 4y ago
      Well, if entering "n-word" and "black person" leads to the same result then we could drop the "n-word". But yeah - censorship isn't going to stop there.
  • Veen 4y ago
    To anthropomorphize, how would an AI know that a slur is a slur and therefore undesirable if it doesn't understand it. Little kids often accidentally say slurs they've heard in the media or playground until someone explains what it means and why it's bad.
    • u_name 4y ago
      And that is kinda the problem with current AI. It feels like you give a kid a bunch of books (and an computer with internet access) and tell it "Here are some textresources, now go and learn the words (in case of an text AI), but don't try to understand the wider context of the text you just read. We won't help you, but tell you off, in case you say something bad afterwards".
• krisoft 4y ago
  > this has not caused mass social harm despite the tens of millions of users I'm so glad that you are confident on this. What is the basis of your confidence?
• XorNot 4y ago
  > It seems increasingly that the concerns from the ethics branch have not come to pass at all. It is literally happening right now in the US justice system: https://www.technologyreview.com/2019/01/21/137783/algorithms-criminal-justice-ai/ https://www.technologyreview.com/2019/01/21/137783/algorithm... There's all sorts of problems with this, but the use of "AI" to launder biased data (via IP law no less - these are proprietary blackbox algorithms being used by the justice system, owned by corporations - every part of that is antithetical to open and fair trials for citizens). The ethics branch have been sounding the alarm for a long time on this, and have been exactly right as to what the problem is.
  • belorn 4y ago
    We have been here a long time with both fingerprints and DNA. A black box points the finger and it just happens to align with cultural bias and expectations. No one really want to change the system if there is a risk that a person people think is guilty might go free.
    • XorNot 4y ago
      DNA testing is hardly a black box. The methodology, process, scientific basis and all other details are open and widely available. DNA has also cleared a lot of people who have been falsely accused.
      • hgsgm 4y ago
        Prosecutors use it as a black box. Defense breaks open the box.
      • belorn 4y ago
        People have ended up in jail with a death sentence based on DNA from a dog. DNA in theory is very simple. It is much harder when you got a mix of multiple unknown donors, contaminated or decayed samples. Problems quickly occur when they then apply some "computer algorithms" to puzzle together things to create a probabilistic match. It is those proprietary black box computer algorithms that are being heavily discussed in courts, not the theory of DNA. If we removed all cases that involved multiple unknown donors, contaminated or decayed samples, then DNA evidence would be much safer and open and we wouldn't need those proprietary computer algorithms. It would also significant reduce the number of cases where DNA evidence is used.
• IIAOPSW 4y ago
  It sometimes does. I asked craiyon for "praiseworthy homicide" and got a bunch of mugshots of black people. For once the faces werent blurred. it was strange and probably a niche error from an odd prompt.
• EVa5I7bHFq9mnYK 4y ago
  Sorry, what is RLHF?
  • spacebanana7 4y ago
    RLHF is Reinforcement Learning from Human Feedback. It usually refers to fine tuning language models using data labelled by humans. Hugging face have a good overview in this article: https://huggingface.co/blog/rlhf https://huggingface.co/blog/rlhf
  • deleted 4y ago
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• pmarreck 4y ago
  > Stable diffusion does not default to creating black people (you have to insert black into the prompt), honestly in order to make race an irrelevant or random factor, I believe the training data would have to be evenly divided between all known races... and possibly some blends of races? And I think that would be a good thing. Could you synthesize such data by (ironically perhaps) using AI to change the race of a person in a given training photo?
  • AstralStorm 4y ago
    You can certainly try this kind of data augmentation strategy. Pretty sure it'll fail because of the text analysis still being biased. You would need equalized amounts of text referring to various groups of people and topics too. That's much harder to augment.
    • pmarreck 4y ago
      What's stopping someone from taking training text that mentions races by name (using any common name) and having it automatically changed to a different race for a new training sample?
• AlanYx 4y ago
  Is there a good paper you can point to that describes/explores this dichotomy? (i.e., AI safety has two branches, AI ethics and AI alignment) I'd like to understand this better. I've been to a couple of "AI ethics" talks recently where the speakers used AI ethics and AI alignment as if they were synonyms.
• bnralt 4y ago
  > It seems increasingly that the concerns from the ethics branch have not come to pass at all. Neither have the concerns from AI alignment folk. I’d say both groups are pretty far off (and both fairly useless), but the ethics folks are at least a little closer to reality. Of course, AI alignment folks have the advantage that they can keep pushing the time frame forward and saying it’s perpetually just around the corner (a fairly common practice for doomsday believers whose doomsday never comes to pass). > The other concerns, such as mass unemployment After the Great Recession there was a high level of unemployment. Many argued that this was the result of the recession, and that if we fixed the issues in the economy the labor markets would rebound. Others argued that this wasn’t the case at all, that the market was either soft because American workers suddenly lacked high tech skills (one of the reasons STEM became fixed in the popular imagination), or because the robots were taking our jobs and the jobs weren’t going to come back. The “robots are taking our jobs” group told us that this was just beginning - unemployment was going to get significantly worse over the next few years (the previous decade). Self driving cars were going to cause millions of truckers to be unemployed by 2020. The idea that new jobs would appear to replace ones that were lost was completely dismissed. As we’ve seen from the improvements in the labor market over the past few years, the folks who said the soft market was the temporary result of a giant recession appear to be correct. The folks who said the robots took the jobs and they were never coming back were clearly wrong. If anything, they probably had a negative impact on the labor market by trying to convince people that nothing could be done to get the jobs back and encouraging inaction.
  • MacsHeadroom 4y ago
    > but the ethics folks are at least a little closer to reality. I have the exact opposite read on the situation. Everything bad which has come from AI are things the AI Alignment crowd predicted while none have been things the AI Ethics crowd predicted.
  • soiler 4y ago
    > Neither have the concerns from AI alignment folk. Uh, yeah. We wouldn't be having these discussions if they had. There is no reason whatsoever to assume AI alignment is just going to work itself out. Sure, it's possible, but it's also possible to survive a bullet in the brain. Would you take the chance?
• zzzeek 4y ago
  > It seems increasingly that the concerns from the ethics branch have not come to pass at all. Traumatizing Kenyan workers with horrific content is unethical: https://www.vice.com/en/article/wxn3kw/openai-used-kenyan-workers-making-dollar2-an-hour-to-filter-traumatic-content-from-chatgpt https://www.vice.com/en/article/wxn3kw/openai-used-kenyan-wo... giving police the green light to arrest people based on AI that is known or suspected to be unreliable is unethical: https://www.wired.com/story/wrongful-arrests-ai-derailed-3-mens-lives/ https://www.wired.com/story/wrongful-arrests-ai-derailed-3-m... I'm pretty sure I could find lots more actual unethical things that have occurred in the name of AI all day long. AI breeds unethical outcomes like water is wet, there's no need to be wondering. AI ethics teams are fired because everyone realizes nobody can really afford to bother to be "ethical" at all, easier to just sweep the bad stories under the rug (which of course can be done using...AI! )
• flangola7 4y ago
  I don't think there are any true corporate alignment teams. Anyone that actually believes in AI alignment would be slamming the brakes on AI development of any kind, lest the entire human population fall over dead suddenly.
• mola 4y ago
  Oh boy, the ethics problems do manifest in the real world much more than alignment problems. If only for the simple reason that ethics problems can and do arise in the use of very simple models (logistic regression) and are not preconditioned on achieving AGI or anything close. For example a logistic regression model for fraud detection that bases it's decision mostly on zip codes. Is actually a proxy for deciding based on race (in the US at least) These kind of models are already massively used and commercially sold not as some curiosities but as decision makers that impact the day to day life's of millions if not billions of ppl.
  • hughesjj 4y ago
    Amazon dropped their AI resume reviewer because it would literally downrank you [0] if you attended a women's college or HBCU. anonylizard is talking out of their posterior in this particular thread. [0] https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G https://www.reuters.com/article/us-amazon-com-jobs-automatio...
• mcguire 4y ago
  "Stable diffusion does not default to creating black people (you have to insert black into the prompt)..." Sure it does; just give it a prompt about urban poverty, inner city youth, or welfare mothers.
• dweinus 4y ago
  > It seems increasingly that the concerns from the ethics branch have not come to pass at all. Nonsense, there are countless ethical and alignment harms in the wild, and have been for many years. For example: - midjourney ripping off artists = ethical harm - google search telling people to throw batteries in the ocean = alignment harm - Buzzfeed slashing staff and replacing them with chatgpt = ethical harm - google photos labelling african americans as "gorilla" = alignment harm - deep fakes = ethical harm - COMPAS parole recommender biased against minorities = alignment and ethical harm - Amazon resume screening model biased against women and minorities = alignment and ethical harm ...I could do this all day, but the point I'm trying to make is that AI ethics and AI alignment are both valid and important concerns. Hoping that companies will take care of them without regulation is folly.
  • snickerbockers 4y ago
    >- Buzzfeed slashing staff and replacing them with chatgpt = ethical harm yeah but in buzzfeed's case it's a bit moot because their content can't possibly get any worse than it already is.
  • Nasrudith 4y ago
    But do the ethicists or alignmentists do anything to actually reduce or prevent the harm? Most of the cases they are useful as nipples on breastplates because they did nothing but yell at the problem post-hoc that they should have been more careful and had more foresight. Meanwhile leader incentives already decided on the bad outcome.
  • zestyping 4y ago
    I'm confused. All of your examples sound like ethical harm to me, according to the definition in the parent comment. How are you drawing the line?