Let's not confuse an ethics team with HR. The later exists to ensure proper legal adherence with a varying degree of benefit to the employees. The former[1] is an electively instated position that usually has a dual mandate somewhere between the polls of "Make leadership confident that teams don't make them lose sleep" and "Make teams confident that leadership doesn't make them lose sleep" (usually leaning strongly towards the second) as a sort of employee moral assurance team. I don't disagree that the ethicist is partially there to justify actions but they're mainly there to be seen as an obstruction to particularly egregious actions so that, if, for instance, you have a boring data center maintenance job, you can have the belief that nobody is using the product of your labor to for something heinous. The efficacy of such teams is quite questionable but there is some logic in assigning the job of worrying about ethical considerations to one person that can shove their nose in every crack and cranny so that every individual employees can talk to/lean on that person instead of needing to go to such lengths themselves if they feel compelled to do so.
Most people don't like to do evil (even if the money is good) so allowing an economy of scale around morale reassurance is rational. This obviously breaks down if the company is seen to hide things from that department or if that department is clearly, themselves, unethical. The first of those conditions are why ethics departments at Meta and OpenAI have very little efficacy.
1. Outside of extreme circumstances where it has been mandated to be a specific regulatory board because of past actions or fear of future actions in which case it's better viewed as part of the bureaucracy of the governing body (usually the state, sometimes a shareholder or other concerned party).
Lets assume one of two worlds - one where AI is constantly improving and one where the tooling is a dead end. In the first world the AI generated comments are no better than the commentary that would be generated in the next six months - in the second world the AI generated comments will obscure the human written comments.
In what world are AI generated comments actually value adds?
If the AI (or the person) ran into a non-obvious constraint, or some externality, or there’s a plan that just isn’t implemented yet- then the comment wouldn’t be able to be divined by the AI. But yeah just pointing the AI at something and saying “write me docs” will get you something at best equally good as what’s going to be available.
In this context they're not the same thing. Calls from companies legitimately operating in the country need to obey laws or face enforcement (ideally, unless the government is asleep at the wheel) while calls from scammers outside of the country are breaking a bunch of laws anyways so who cares about violating a do not call list.
I consider marketing is a plague on attention and view it highly negatively - but in the case of tools to reduce unwanted phone calls there are some real differences in what's available to legitimate vs. scam callers and a do not call list can only ever be effective against people working within the system.
It suffers from an ends-justify-the-means trap where bad actions in the short term with the long term goal of good actions are justified by the fact that you, the actor, know your philosophy is the best way to enact positive change.
I'm happy to try and get already wealthy individuals on the train of effective altruism but it has been used to justify wealth concentration far too much and, to be honest, spreading money around is one of the most effective ways to enact real positive changes in the world since individuals know their own situations the best.
EA is probably too broad of an umbrella. I think there's a distinction to be made between trying to find the best per dollar donation (givewell etc) and people who use it as justification to amass wealth. That said, most of the people I know who declare themselves effective altruists also openly state that the world would be better off if all the wealth and decision making power were concentrated in a small group of hundreds of people who are "smarter" than everyone else. They tend to think that they would belong that group. Anecdotal, but it does make me skeptical whenever I meet someone who uses EA to describe themselves.
Moving elements on screens is viewed as slick but is also a strong statement that the website knows how it is best to consume itself and depriving the user of the control over how to interact with it. I think there's been a big misunderstanding from UX designers about what features users actually value over time and too great a reliance on short window A/B UX comparisons where the cool effect of animations has not yet worn through.
This is also complicated by the fact that _all UX changes are bad_ until the users get used to them. So if you genuinely believe you're providing a better UX you do need to ignore the initial wave of negativity - which makes it difficult to tell knee-jerk reactions from genuine criticism if you're glossing over the results.
This is probably (if the business here is large enough to support it) an excellent area for a tailored model instead of a general purpose LLM. A lot of the context around medication comprehension is going to be rather universal to pharmacies and other HCPs so ideally that information would be baked into the model itself with the actual user supplied context mostly being focused on business specific logic. The commodity LLMs are just an amalgam of a hammer welded to a screwdriver, a car, a compass and a toothbrush - more specialized models, with more specialized testing and offered by a company specialized in the field would possibly offer a decent customer experience here?
With something like healthcare though I'll remain eternally skeptical that anything other than a licensed expert will be palatable to the public.
There were some brief excellent years in the nascent days of the blogosphere where stories that CNN would miss (especially stories about marginalized groups) managed to get widespread attention and the compensation to journalists held up. But where we are today in terms of news compared to the 00s or 90s (even with all the retrospective knowledge about journalism catastrophes like NYT's coverage of the Iraq War) is so much fundamentally worse.
Journalism, if done correctly, is unprofitable - the times in American history it has thrived, imo, have been when journalists have been patronized by people willing to trade money for prestige. That could have happened with the WaPo but now it appears to be more convenient to have a mouthpiece even if it's obvious to everyone.
Organizations like NPR and the CBC that get government funding can survive a while, but inevitably an administration will come into power that will threaten them or outright deny their funding to the point of impotency. Still, given how cheap they are to us in terms of a national budget it feel like just diverting 5% of the DOD's unmarked funding to just throwing money at journalists with no strings attached would probably result in immense transparency and quality.
> Journalism, if done correctly, is unprofitable - the times in American history it has thrived, imo, have been when journalists have been patronized by people willing to trade money for prestige.
I agree with the first part of that, but not necessarily the second. For a very long time in America good journalism was essentially paid for by classified ads. They were really two separate (but obviously related) businesses. Journalism could be more "walled off" from the money making side of things since classified ads were bringing in money hand over fist.
The Internet decimated the classified ads business, so now you see more sensational stories that try to make money in their own right. Even on the CNN website, there are ads at the bottom that are confusingly meant to look like stories. They're often embarrassingly dumb (literal "the one trick doctors don't want you to know" type of stuff), but I think that's what it's come to for news businesses to survive.
> If the model labs aren't clearly profitable, or open source models eat all the 'model layer' profit - what financial force will push forward very expensive experiments/scaling, etc.?
It's hype - when the hype dies the great push will slow.
My hypothesis is that we'll end up with something like Seti@Home where continued model training gets outsourced to a benevolent appearing product (something like what OpenAI started out as). If I were to bet - Europe and Canada seem best poised (especially the latter) to produce an AGI initiative with a strong ethical focus.
Drug names are frequently BS loaded with strange consonants without singular pronunciation guidelines (sadly English isn't German) so humans already have a lot of variation in how things are pronounced - models then need to comprehend those variations, regional dialects (like those fuggin' ahs from Boston).
Wow, those names are actually real. They sound like fly-by-night compliance "brand" names on amazon sellers. How did those get approved by a multi-billion dollar marketing team?
They need a name they can trademark, and common words can't be trademarked. It's sort of a .com domain name problem, all the good names are already taken so you just go for something you hope is pronouncable.
This, I suspect, is exactly like offshoring - and a lot of companies died during the offshoring fad because their software products become full of low quality merges and feature improvements that the company couldn't afford to fix or remove by the time they realized there was a problem. That remains my primary concern with AI code generation - well established codebases might become full of slop to the point of being unusable without a clear path back to maintainability leading to company death.
There's precedence for new versions of software being abandoned for older code bases... usually the new version doesn't ship or gets forked relatively quickly though, e.g. the Windows Longhorn reset or the Gnome 3/MATE fork.
It can happen - and companies can recover from that. But that's wasting a whole lot of money and a lot of executives will sunk cost fallacy themselves into continuing when that may be the much saner decision.
I didn't mean to imply that all companies that went hard into AI will die - just that a lot of companies that follow the trend may not realize the true maintenance costs and of those that did misguidedly follow the trend I'm sure some will luck or manage their way out of disaster for various reasons.
Most people don't like to do evil (even if the money is good) so allowing an economy of scale around morale reassurance is rational. This obviously breaks down if the company is seen to hide things from that department or if that department is clearly, themselves, unethical. The first of those conditions are why ethics departments at Meta and OpenAI have very little efficacy.
1. Outside of extreme circumstances where it has been mandated to be a specific regulatory board because of past actions or fear of future actions in which case it's better viewed as part of the bureaucracy of the governing body (usually the state, sometimes a shareholder or other concerned party).