lemmsjid

I'm a supporter of free speech, and like most free speech supporters I tend to believe the suppression of speech leads to a paradoxical effect: the metastasis of the suppressed ideas.

Of course there is a but coming! When twitter launched, I immediately felt like Twitter itself was a distillation of a fascistic impulse: the idea that a curt and pithy phrase, stripped of nuance, is not only a superior way to communicate, but the only way to communicate. (I'm using "fascistic" here not to incite, but for lack of a better term: I think everyone has an impulse towards the safety of political simplicity, and that modern democracy is founded on complexity, i.e. lots of opinions, lots of checks and balances, lots of persuasive argument required to achieve things). I feel that the very structure of throttled meaning is what made Twitter in particular such a platform for mass outrage and negativity.

Fast foward a decade, and the twitter model of simplicity is now the normal mode of discourse on social media. If something is not a few seconds long, its reach is quite limited. This means that simple things, like propaganda, are easier to articulate, and complex things that acknowledge the subtlety of actual life get buried.

Taken out of political context, a good example is videos of altercations between people (fights, arguments, etc) that become viral. As a viewer, I almost immediately feel outrage and righteous anger against the perceived victim of the altercation. But sometimes some context comes to light: the perceived victim is actually the aggressor, or the situation is much more complicated than it seemed. Putting this back in the political context, I see quick videos getting passed around that do a similar thing: take an event quite out of context in order to manufacture outrage against a particular group. Of course there is a word for this: propaganda.

I'm not a technological doomer: I'm quite intrigued as to what is happening, and my impulse is not to shackle it. But what I'm witnessing is that propaganda (or otherwise, events taken out of context) spread like lightning on social media, and I am sympathetic to attempts by platforms to somehow provide context or moderation to that spread. The mob mentality is real. I share the Mayor's concern about Twitter, because even though it was a sewer from the start, in my estimation, by its platformization of epistemological constraint, the fact that it is walking back attempts to staunch the spread of its own demons is concerning.

I do think a healthy public debate in a functioning, free speech democracy, is essential to its lifeblood. But for that debate to function, it must be done in good faith, and with some shared understanding of truth and context. While I see that happening in some places on social media, it's generally on well moderated forums in which people accept that bad faith arguers will be banned.

Like I said I don't have a clear sense of the solution to all this. State sponsored propaganda was all too effective before social media, and I can see social media undermining the monopoly of the state on the dissemination of that propaganda. But perhaps the pendulum will swing too far to the other side, where blatant bad faith, grassroots propaganda, and untruth successfully steer public opinion.

To me this blog post doesn't fully make its case, though has many good points and is a good read.

I think my main logical objection is that the alternative best practices at the end of the article were all security best practices before WAFs existed. Which makes me ask the question, why did WAFs come into existence in the first place? Did the founders of those companies convince customers they needed them without those customers actually need them?

I think not. In the years before WAFs existed, I was in the position more than once of being in an organization whose web application security footprint had grown to the point where we ended up writing a home-grown version of a WAF. E.g. adding an interception layer that would analyze inputs and outputs for typical security violations.

Why? Well, first because it started to give us a sense of the types of attacks that people were trying to use. Second, because the types of mitigations mentioned by the author of this blog post aren't the whole story. You can audit that your entire system avoids SQL injection attacks via stored procedures, then your company buys another company with a code base that fails such audits. Or someone attacks by leveraging your caching layer which stores and sends back unaudited key-value pairs. Perhaps (this has happened to me) a bug gets introduced into the deployment system, and the code that forces authentication is not shipped, and the calling code doesn't properly fail when the auth checking code isn't in there. A real head slapper in hindsight.

I do like the best practice of process isolation around APIs, and only allowing APIs to have the privileges they require, but in practice, if there are hundreds of APIs undergoing frequent changes, the complexity of managing that becomes a security risk in and of itself, because the ACL rules are deeply complicated.

Relying solely on a WAF seems like a bad practice. But also relying only on secure design philosophy is a practice with plenty of historical failures.

So if the point of the article is that WAFs breed complacency, I agree with that! But if a WAF is used as an analysis, auditing, and fast-response layer, alongside following secure design principles, then I'd say that based on personal experience, if WAFs didn't exist, people would write home grown ones with their own sets of flaws.

My instinct from your response is that if we chatted on this for a bit in person we'd see eye to eye and we're probably thinking of different use cases, because I can see how thoughtful you are and usually it comes down to thinking about particular problems in particular companies. So at the risk of going back into crass generalizations, I do persist in thinking that the TCO of a monolith is lower under a lot of the constraints you're describing, assuming (big emphasis) the tooling of the language you're using for the monolith, i.e. a combination of linters and compiler, can enforce the rules. I've been in service-first environments where the equivalent of not caring about code quality in the monolith is firing up a new service without consideration for refactoring the older service, until I am in endless architecture meetings about how to make cross cutting changes around a bunch of services everyone regrets creating.

I suppose in the end it comes down to the classic issue of needing to pay down of tech debt, which is true in any software ecosystem.

It isn't just the tech illuminati who associate Bitcoin with scams. Everyone in our neighborhood now knows that it's a regular occurrence for older people to get emergency calls from the "gas company" and rush to the corner store's Bitcoin kiosk so they can pay and not get their gas shut off.They then realize it was a scam and post on Nextdoor, Facebook, etc. While I know that cryptocurrency is not a scam, and while I know that such scams pre-exist Bitcoin, that is absolutely the perception that it's getting in our community amongst non-tech people.

Your edit, BTW, is interesting. You tar all the responses with the same brush, "missed the point", "lack all imagination", and then accuse them of having a condescending tone? Do you have a sense there might be a two way street? While you do have a point, there's a lot of reasons why human dishonesty, e.g. scamming, prevents us from having a great many nice things that we could otherwise have.

The assumption behind why you'd use the program is that you have access to a proprietary dataset of sufficient size to build a large model around (say, for example, call center transcripts). This almost certainly means OpenAI doesn't have access to train their other models off that data, and it almost certainly means your customers can't take the same data and go straight to OpenAI.

I'm assuming that the target customer of this is people whose moat is proprietary data. If their moat is a unique approach to building a model, then it would indeed be dangerous to engage OpenAI. But then I'd think OpenAI would be hesistent to engage as well.

Interesting--perhaps the AI detectors are right, and this will be how we discover that we are in fact in a simulated universe!

Yep. Mentally it's rather like the unpredictable behavior you'd get if an API server was passing code to the client for it to execute.

You can do the same with the approach I described. If you set up the modular DAG as I mentioned above, you can now set up service boundaries between the leaves of the DAG. E.g. parts of the code call other parts of the code as a service. You then version and deploy the same codebase separately.

Say you have Libraries A, B, and C, where B and C depend on A and not one another. You can have B call into C via a service, just as you would in a microservice. Now B and C can be versioned and deployed independency. You can also deploy updates to Library A incrementally, tying it to the B and C deployments.

If you are literally pushing different features that are in fact unrelated, you don't even need to worry about B calling into C, you can just partition your app into different modules, deploy them separately, and use a load balancer with routing rules to arbitrate between the deployments.

I like having this type of environment because you can make fairly quick and easily-resersible decisions about whether or not different parts of the codebase are deployed differently: sometimes it's compute and hardware requirements, sometimes it's because you want parts to be stable and other parts more experimental and volatile.

The microservice argument isn't addressing this type of deployment scenario: it's suggesting a shared-nothing or shared-little architecture across services.

Good show for mentioning that. If it becomes commonplace for popular runtimes and languages to be able to load modules and their dependencies at that level, then a lot of arguments for service encapsulation go away.

I think in these discussions, a lot of times people are taking past one another. If I start putting a JRE-targeted application together, I know I can eventually reach for isolated modules if I follow good internal practices, whereas if I'm in Python land it's pretty unattainable.

Yes, a good point, I think the more dynamic the language, the more one gravitates towards microservices as a problem solving tool, because you'd give up a lot of the value of the dynamic environment by enforcing strict rules.

Though I'm seeing a lot of convergence between environments over time, which makes me think we're all headed towards a nicer future.

For example in Scala, which does a lot of type inferencing, it's typical to tell the linter to require that public methods have explicit types, even though the compiler will reify them at compile time anyhow, because that makes the interface much more robust to refactoring. Meanwhile in a more dynamic environment, in Python it's getting more typical to use type annotations, and, similarly, to especially use them on functions that define a reusable interface.

I figure that the ideal languages in the future have module-level systems where they can define strict interfaces across modules, but then get as crazy and dynamic as they want inside of the modules.

Well now that you mention it I think it does all come down to 'separating data from logic'. I was working backwards from the premise of: "what if we want a monolithic in-process application to have the same cognitive simplicity as an API-based client-server model?"

If you want to enforce a clean interface between an in-process client and server (i.e. a piece of code calling a library interface), then the best model is to think of it as a message passing system, where once a payload is passed from the client to the server and vice versa, the other side should not be able to witness changes to the payload. An immutable payload in this context is the same as the json that goes over the wire between a client and server.

If you really wanted an in-process application to look like a microservice you could take the added step of forcing a serialization / deserialization step on both client and server. I've seen frameworks that do this. But I think immutability, if it can be enforced, is a practical way of solving this problem and far less complex.

Inheritance is a hazier point I was making, in hindsight, because you could use inheritance for data modeling, which is quite fine in some situations... so I think it's effectively subsumed under the "separating data from logic" argument: which is that if you're passing behavioral inheritance from a "server" to a "client", then it gets harder and harder to predict how that client is going to use it and thus it's harder to reason about the functional boundary between two pieces of code. But it's a hazy point because I think the larger and more important point to make, as you point out, is that you simply shouldn't (in most cases) pass any kind of behavior between client and server--just data.

Another approach to look at (besides taking inspiration from Smalltalk) is the actor model, where it's incredibly clear that any communication between modules in an ecosystem is immutable messages. In fact a side effect of the actor model is that it gets pretty easy to move things from in-process to cross-process because most activity in the system is already performed through message passing, so you can just start channeling messages from Actor A to Actor B through a serialization/networking layer rather than in-process if you want to deploy them separately for reasons of convenience or computational needs.

If the monolithic application is written in a language with sufficient encapsulation and good tooling around multi-module projects, then you can indeed have well known and encapsulated interfaces within the monolith. Within the monolith itself you can create a DAG of enforced interfaces and dependencies that is logically identical to a set of services from different codebases. There are well known design issues in monoliths that can undermine this approach (the biggest one that comes to mind is favoring composition over inheritance, because that's how encapsulation can be most easily broken as messages flow across a single-application interfaces, but then I'd also throw in enforced immutability, and separating data from logic).

It takes effort to keep a monolithic application set up this way, but IMHO the effort is far less than moving to and maintaining microservices. I think a problem is that there's very popular ecosystems that don't have particularly good tooling around this approach, Python being a major example--it can be done, but it's not smooth.

To me the time when you pull the trigger on a different service+codebase should not be code complexity, because that can be best managed in one repo. It is when you need a different platform in your ecosystem (say your API is in Java and you need Python services so they can use X Y or Z packages as dependencies), or when you have enough people involved that multiple teams benefit from owning their own soup-to-nuts code-to-deployment ecosystem, or when, to your point, you have a chunk of code that the team doesn't or can't own/maintain and wants to slowly branch functionality away from.

Why do you summarily dismiss (and recommend that other people dismiss) the multiple viewpoints in the article suggesting that the law you’re mentioning was unfairly targeted at immigrant owned establishments? It’s absolutely part of the story. Is it really that hard to believe that a corrupt way of enforcing a law might intentionally be targeted at people who are less likely to feel empowered to fight it?

I think the core of our disagreement lies in your statement here: "You don't understand scientists then. They don't want to be "set for life". They want status within their own bizarre little community." I know some, but not all, scientists, and I can't put them firmly in that category. They're motivated by all sorts of things, as are the rest of us. I do know people who have left academia because they came to hold this belief through negative experiences, but I also know people who have avoided such. I don't think I or you can presume to make such sweeping pronouncements on such a large and varied group of people. I also believe the idea that contrarian scientists immediately lose their career when they question the status quo is an easily falsifiable claim. Is there a general pressure to conform to group think? Yes. Are there painful trends in academia? Yes. Behind the current state of climate science is quite a bit of evidence. I am open to it being entirely wrong, but it seems quite a bit more likely to me that it is right, at least correct enough to take action. The consequences of taking action are far lower than the consequences of not taking action.

I've read a version of this line of thinking many times.

You do realize that if a scientist could put up a reputable set of studies that disprove the central climate change theories that they would be set for life under a cavalcade of fossil fuel sponsorships. Not to mention that they would be a hero to most of the planet. They would be singlehandedly responsible for major policy shifts on the part of entire countries. There's a massive incentive for someone to convincingly disprove the negative effects of climate change.

If there is such a complete and totalizing suppression of actual inquiry in climate science, then why are there climate skeptics with positions in major universities? Why are major journalistic publications skeptical? It seems to me that there is quite a bit of a forum for debate on climate science, because everyone, including, probably, many climate scientists, would love for it to be wrong.

Your argument is based on your being completely convinced that a very large swath of people, many if not most of whom are parents like yourself, are acting in utter bad faith. Certainly any academic field, like any human endeavor, is subject to group think, but if you look at the very real scientific progress that's happened in the last several hundred years, you can see that the scientific approach, empirically, does lead to success, or at least disproves the notion that groupthink is likely to wholly capture a scientific field.

The politicization of the whole thing ("liberal morality") is also intriguing. I'm an unabashed liberal. If you put a convincing argument about how the climate would be fine in front of me, I would thank you a thousand times over.

As it stands, I've read so many arguments from climate skeptics, and they roughly follow the following templates:

* a wholesale belief that climate science is operating under a special kind of bad faith

* misunderstandings of things like the second law of thermodynamics (e.g. ignoring the atmosphere itself acting as a heat sink)

* belief that Professor Q is somehow right and all the other professors are wrong (probably because of the bad faith part), ignoring that Professor Q might also be subject to such things

* belief in government or corporate control over the discussion, ignoring the truly massive financial incentive to ignore climate science

* citations, usually exaggerations, of how many "climate predictions" have gone wrong, ignoring that science journalism and activists will often simplify and/or incorrectly cite studies in any field, because the public doesn't, in the end, understand the language of probability

While I’m a democrat, I don’t believe republicans or democrats are inherently better people, or that their overarching ideologies are inherently better. In fact I am a strong believer that absolute power corrupts absolutely, and neither republicans or democrats should win it all.

That said, certain Republicans should very much feel shame about the fear mongering behind the vaccine. It isn’t automatically a hot take or a lightning rod to use statistical analyses to suggest that systemic fear mongering against a vaccine that has a powerful effect would lead to excess death.

The vaccine long ago became a political issue, but the real world need for people to take it doesn’t go away because of that.

I noticed he mentioned asking Bing, so I directly asked ChatGPT “who is Ryan McGreal?” and it wrote, “ Ryan McGreal is a writer, urbanist, and the editor of Raise the Hammer, an online publication that focuses on urban issues, transportation, and sustainability. He has been actively involved in advocating for better urban planning and transportation policies in Hamilton, Ontario, Canada. Please note that my knowledge is based on information available up to September 2021, so there may have been developments or changes in his work or activities since then.”

That appears more or less correct

So to give chatgpt an opportunity to hallucinate similarly to the article, I followed up with, “Did he write for the nyt?” and it replied, “ I do not have any information indicating that Ryan McGreal has written for The New York Times (NYT). His work primarily focuses on urban issues and transportation, as mentioned earlier, and he is associated with Raise the Hammer, a local publication in Hamilton, Ontario, Canada. It’s possible that he may have contributed to other publications, but I do not have specific information regarding his contributions to The New York Times.”

While I have seen ChatGPT make stuff up I do think it’s useful to compare specific results across LLMs before using particular examples to make holistic statements.

One of the initial proponents of public education in America, Horace Mann, saw education in a two pronged manner.

First, a functional democracy requires that the citizenship be well informed and capable of critical thinking: "A republican form of government, without intelligence in the people, must be, on a vast scale, what a mad-house, without superintendent or keepers, would be on a small one."

He also saw the economic side, saying that education was an equalizer for people in terms of helping them to reach their full potential.

I quite agree with his assessment. In a system where everyone has a vote, it becomes quite important that everyone have a sense of things that extends beyond their career vocation. His imagery of an uneducated republic being a madhouse makes much sense from this perspective.

Insofar as we have given up any optimism about the democratic enterprise, then certainly we could look at education as purely to put people into economic bins, but at least in my own public school education in the US, every student did get significant doses of math, history, science, etc., outside of their expected career direction.

This to me suggests that there is a tension, not fully resolved and HOPEFULLY never fully resolved, between education-for-economics and education-for-democracy. I think it's quite pessimistic though to give up the ghost on the education-for-democracy aspect.

I think it's important not to lie, but I don't think the above is automatically a lie. Instead, it's a call to evaluate people on multiple dimensions rather than one.

When you're giving feedback to someone, it is often a knee jerk thing to ONLY evaluate the outcome of their work. The other thing you should evaluate, though, is your estimation of their effort, e.g. how hard they worked at it, and your estimation of their process, e.g. how well they used their time.

If you only evaluate the outcome of their work, and the work is not adequate, you have given them a purely negative evaluation. If you acknowledge respect for their toil and their process, then you have given them 2 positive evaluations and 1 negative evaluation. You're also acknowledging that because you respect their toil and process, they are doing the right thing in spite of needing the course correction you are providing.

Of course, maybe you have a negative opinion on all 3 aspects of the evaluation. If you think they didn't apply themselves, e.g. their effort was not good enough, AND you think they were't efficient in their process, AND you think the outcome was bad, then certainly it would be a lie to praise any of those aspects, though at that point there's almost certainly something more fundamental that's going on and the person is not a good fit for the job.

Finally, it's important to evaluate your own sense of certainty about the feedback.

I think the important thing about the above advice is that if you are giving feedback and you only focus on the course correction part, it's safe to assume that most people will take that as negative feedback on all the aspects of their work. Now, there are situations and teams where there is so much trust built up around everyone's mutual respect that you can skip to the outcome feedback. There are also feedback-recipients who are confident enough in themselves that they feel that they don't need anything but correctional feedback. In other words, "This was shit!" can totally fly when there's a lot of mutual trust and confidence. But too often I've seen people misread the room in that aspect: THEY, the feedback-givers, have plenty of psychological safety, and they think that is extended to other people who absolutely don't feel that way.

I don't wholly disagree with you, and in fact think you have a very good and thoughtful perspective (FWIW), but I do have some thoughts.

I think there's too much focus on advertising and corporate interests as the thing that undermines journalism. There's such a thing as to little focus, but right now there's too much focus.

For example, I have seen people lionize particular doctors, or researchers, or climate scientists, or what-have-you, who hold contrarian opinions on particular subjects. Clearly those people, in the minds of those who lionize them, have fewer conflicts of interest than advertising-driven journalists or powerful government officials.

The problem is that there are powerful motivations for people to lie or deceive that are equal in power to advertising money. Power through influence. Power through self-righteousness.

For example: I've looked into various vaccine conspiracy theories that have been touted online, and some of them come from highly credentialed people, sometimes with excellent historical track records in medical fields, who none-the-less are playing fast and loose with the data, or drawing conclusions that cannot be backed by research. The people who tout those theories look to those originators, those highly credentialed people, and say, "Look, there's Dr. So and So, they aren't part of Big Pharma, so they must be on to something". Then I look into Dr. So and So's blog, and look at the research they're citing, realize they're misinterpreting, or exaggerating, or what-have-you. In short, they are deceiving the public. They aren't financially motivated to do so. So why do they do it? Well, there's plenty of reasons. A desire to be right. A desire to be relevant and respected. A desire to have an audience. I think these things are easily as powerful, and often more powerful, than advertising money held over a journalist at a large media company.

And I see benefits to journalists working in groups with editorial control. I've seen great authors go astray in terms of quality when they start self publishing, or somehow become influential enough that they can shrug off their editors. I believe any journalist would be subject to the same forces of ego, influence, etc. If a journalist is making their money through Substack subscriptions, that may be even more of an existential threat than one faced by a journalist at the NYT, who can more readily absorb the financial hit of a story that goes nowhere. The subscribers, after all, now have expectations of what they will get from that journalist. Juicy stories -- at any cost?

Aren't we all a bunch of amateurs hiding our lack of true expertise? Each passing decade I feel that all the more. I think you've described the human condition.

The larger news outlets are some of the few remaining places that actually hold their news rooms to some kind of factual standard and facsimile of objective reality. If NYT or the Economist or the BBC tells me the sky is blue, I'm pretty sure it is. If they report on some scientific topic the reporter is not an expert on, I understand that there's probably some signal lost. If they publish something on a contested political topic, I understand there might be some slant in the direction of their overall political leaning. I also understand that they have an interest in the direction of their corporate ownership and host country. But there are plenty of other outlets trying (and succeeding) at capturing audiences who have all those same conflicts of interest, and more, but do not hold themselves to a factual standard.

While media companies have indeed "eroded their own credibility", in that there's a steady stream of falseness alongside truth, I would add with equal measure that "their credibility has been undermined by others". The loudest voices that castigate the media, in America at least, tend to be the ones that profit the most from being the sole arbiter of truth for their own audiences.

The business model of having an autonomous news room that holds itself to factual standards and is largely sequestered from advertising is shrinking and shrinking. I mourn its death, for I see no replacement coming along.

What if it is apparent that there are other groups pushing the narrative that the media is untrustworthy so that they themselves can own the narrative?

Any given group of humans will have a mixture of deceptive and trustworthy participants. Singling one group out for constant castigation, held against an impossible standard, makes it easier for dishonest members of other groups to avoid the spotlight.

When I first used a modern VR headset, it felt so real to me that I felt like I was truly in the virtual space. It was an amazing and memorable feeling.

After several years of using one intermittently, it doesn't feel any more real than my monitor. My brain taught itself to see all the elements that make it artificial, and while it's still amazing as a technological feat, it no longer feels real at all.

I feel that a similar thing happened to me with the latest round of generative AI improvements. A year ago they felt amazing and almost sentient. Now my brain has started to internalize the patterns in the output, and while I'm still impressed and amazed by the technological prowess and data summarization utilities, it no longer feels amazing.

I think if AI is to truly get a foothold in art, it would first need to have a capacity to generate a new voice and viewpoint and imbue its work with the kind of fresh meaning that separates a good piece of writing from a boring or empty genre work. That said, I do think AI is even now ready to make inroads in 'boring or empty genre work'. When I ask AI to write something, while I don't see artistic merit in the output, I do see the same level of merit that I see in a mediocre human written piece.

I guess if I am scared by anything, it is this: if a great human artist often begins their life building/selling boring and derivative works, and AI displaces the market for paying humans for boring and derivative works, then will fewer artists have an opportunity to first wallow in, and then transcend, mediocrity?

If that is true, then I suppose I am worried, and I understand where Nick Cave is coming from.

Thank you, I'm going to give that a try!

I've taken a throwaway approach to diagramming, where I'll produce them more or less on demand for a meeting or presentation, but not think of them as an enduring artifact. PlantUML is my friend here because I can knock out ugly but gets-the-point-across diagrams in 30 minutes before a meeting and check them into source control, so I can then take the bones of older diagrams and rework them for a fresh meeting.

I used to whiteboard for this, but that hasn't carried over well in the remote world. What I miss about whiteboarding though is that you can tell a story as you draw, so whoever's viewing can watch something unfold from a blank slate while I'm walking them through the history of whatever system we're describing. That said, I can make a PlantUML diagram much more correct than a whiteboard.

All that said I too would love for more of that to be automated increasingly through AI. And I suppose it should make sense conceptually, because for me the value of a crafted diagram over an automated one is that no one really wants to look at the insane ERD of an OLTP database or a production object model. They want the digestible high level vision of the important bits, or the bits that are relevant to the conversation taking place. So it's a summarization problem. How to get the right data to produce a correct summary is interesting--I'm sure if I look there's a dozen papers to read on a similar subject :).

I have had the same experience, interestingly in the same time frame. I felt that when doing Java projects I needed to enter this special telepathic flow-state with my IDE and cut-paste shortcuts and change huge chunks of code every time the model changed a little bit. Transitioning to immutable data classes with functions operating on the classes, and abstractions focusing on what functions operated on them and in what context made life much easier.

Based on the assertions you were making above, I was expecting the study you linked to have to do with cognitive impairment and masks. Its only discussion of masks is a theory that perhaps the fact that test administrators wearing masks might have affected the measurement of the results.

"Although all study visits were performed in-person, the inability of infants to see full facial expressions may have eliminated non-verbal cues, muffled instructions, or otherwise impair the understanding of test questions and instructions. Without direct comparison of performance in the same children with and without face masks, it is difficult to rule in or out the potential influence of masks."

An excellent point and I agree.

There's an oft passed around cartoon where a guy in a tattered business suit is in a cave around a fire talking to children, saying, "Yes, the planet got destroyed. But for a beautiful moment in time we created a lot of value for shareholders."

That cartoon has resonated over the years because it illustrates a point that complexifies the whole shareholder-value concept: you can recognize that a corporation's fiduciary duty is to its shareholders, but you still have a long term / short term thinking problem. If a corporation is just shoveling its profits at shareholders without consideration for the future, or, in the cartoon example, destroying the planet, is it really providing them the best value?

There is no universal definition of shareholder value, legally or otherwise. I'm a shareholder in many companies, and to me they should deliver me profits when it makes sense, take care of their employees, not harm the environment, not overspend, not cut corners on health or safety... it's a long list, really.