I want to make a simple point just for the record...
Compliance (a.k.a. “Business Ethics”) is not Ethics.
As far as I'm concerned...
ethics is to compliance as
bunny is to chocolate bunny.
To me, ethics is an exercise in self-restraint.
It looks at things that are legal and still asks the question,
“Even though I'm allowed, maybe I shouldn't do it anyway?”
By contrast, compliance is an exercise in
manifest destiny.
Businesses decide they're determined to do something and then assign someone,
usually a lawyer or someone they flatter by calling an “ethicist,”
to find any rationale, however thin, that explains why the thing they are already bound and determined
to do should be seen as legal,
so they don't have to slow down or ask permission before proceeding.
These are not the same.
I recommend never using the term “business ethics” when speaking of corporate decision-making.
Always say “compliance.”
I owe a whole essay on the topic of ethics and ethicists.
Since I've not written that yet, I'll just say that
to me, ethics is a hygiene, not a credential. I'm not sure anyone should wear the label,
but especially not those doing compliance.
I'd love to have a job doing real ethics for a company, but I'd have trouble with the title “ethicist.”
I often say of myself “I aspire to be ethical”
because saying I am ethical seems a little too much like I'm confused into thinking I'm there.
It makes me cringe.
I would make analogy to alcoholism, where people say they are sober, not that they are no longer alcoholic. Or to the Catholic church,
where everyone is just assumed to be a sinner who keeps trying, rather than ever declaring themselves to be without sin.
To me, the biggest danger sign of being in ethical danger is believing that one is ethical.
And even if I thought I had somehow gotten there, I would insist on starting each day asking “Am I still ethical?”
Author’s Notes:
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The image generated with help from abacus.ai's
ChatLLM (Claude Opus 4.8, GPT Image 2.5 and GPT Image 2.5 [Edit], which is apparently not the same).
Light post-processing was done in
Gimp
to crop and optimize the resulting image as a .jpg for faster web download,
Wiktionary
says “useful idiot” is a derogatory term meaning
“one who unwittingly supports a malignant cause through naive attempts to be a force for good.”
I find the “derogatory” part to be a distraction.
They're not wrong that people see it that way, but
the part of this that I care about would be equally true if the term was “useful genius.”
I just want a term that gets away from the insult part and focuses
on the tactical aspects of what a “useful idiot” actually does.
I sense that the fuss about intelligence levels keeps people from focusing on
the mechanics of useful idiocy.
Useful idiocy is really about something I lately call ”intent laundering,”
by analogy with money laundering.
To launder intent, one really only needs another person who is suitably oblivious.
There is no specific requirement for stupidity.
Even geniuses can be oblivious,
and so they can easily serve as useful idiots.
What a person of evil intent wants is to be defended by someone
who doesn't see the evil they are defending.
Better still if the defender thinks they see good,
but as long as they're oblivious to the evil, that's enough.
That's because such a person, pure of heart,
is willing to defend evil actions as moral.
Since they don't realize that's what they are doing,
you can interrogate them all you want—even trot out a lie detector—because if they don't see or suspect the evil,
they will defend to the death the good intent of the person or thing
for which they are spokesperson.
I think the “idiocy” part is a cynical view by the evil person
toward the spokesperson they have recruited and duped.
The evil person sees the oblivious person as an idiot
for not seeing the evil.
This condescension is part of being evil.
You start to divide the world not into good vs. bad,
but into smart vs. stupid.
An armchair view of sociopathy
This perceived divide between smart and stupid
seems a core part of being a sociopath.
Some like to think of sociopaths
as irrational. I do not. I am not a psychologist, nor am I appealing to any medical terminology
when I say this, but in my own head I think of sociopaths as intensely rational,
“hyper-rational” is the actual word I use to keep
my internal bookkeeping straight.
This distinguishes them from truly irrational people.
Sociopaths are not unpredictable.
They're very predictable.
What sets them apart is their lack of moral grounding and their utter disrespect for rules.
Regular people don't cheerfully steal from, extort or deceive others
because they are trained that
“good people don't do such things.”
It becomes part of their internal character.
By contrast, sociopaths are good mimics,
so they might say the words “good people don't do such things”
even as their actions say otherwise.
They know the answers people want. It helps them blend in.
But regular people are socialized and caring, driven by a basic sense of fairness.
A sociopath sees these traits as irrational, convoluted, too much work, or the stuff of idiots.
To pick a pure hypothetical, a sociopath might ask “why would one voluntarily
go to war when one can claim they have “bone spurs”
and not have to?” Notions of duty to country do not enter into the reasoning for a sociopath
because, to them, such convolutions only complicate life in what seems to them as irrational ways.
So much simpler to just do what's easy, care only about oneself, and lie when it is most efficient.
And that efficiency, I think, is why sociopaths come to see others, people who are socialized
and empathetic, as “not smart.” They come to see the world as a race for goals by any means.
They scoff at those held back by arbitrary things they find unimportant, like morality and manners.
Oh, they might mimic these things, but only tactically, as a behavior in context, if it is the fastest
way toward their goal. They have no commitment to behaving that way when no one is looking or
when rules obviously can't be enforced.
Manners, ethics, and norms—oh my!
Manners, ethics, norms, morality, and especially law and rights are bundles of rules we get from different
places and integrate into our total behavior. Personally,
I think of ethics as rules we make up for ourselves, manners as default rules between individuals,
norms as default rules for formal situations, morality as rules that come from a life philosophy or religion that
one might subscribe to, laws as stable but changeable rules of society, and rights as rules that are
constraints on laws.
All these differently named, differently sourced, differently encouraged rules
collectively form the complex fabric out of which communities and societies are built, that we may trust one another
and not live forever as creatures of the woods who must kill or be killed. They enable collaboration and cooperation
by making us predictable in ways that are not simply backstabbing.
The celebrated death of norms
I imagine sociopaths see these bundles of rules as sources of inefficiency, things to cut through
with a machete, or else as tools to ensnare and slow down competitors—but not oneself!
They see rules as being things stupid people suffer, and that smart people overcome.
So if others want to handicap themselves in those ways, that's fine for them, but to the
sociopath, rules feel stupid and inefficient.
And don't get me wrong: A lot of us in socialized society hate rules, especially bad ones.
We often wish it were easier. And so there's a bit of hero worship for people who get around them.
We've seen a lot of that recently.
It's an important and unfortunate fact that
while we teach people they must follow rules, we do not as often teach the reason why.
And when rationales are left aside, rules can seem unmotivated.
That means the important role rules play
in society can seem distant or inaccessible.
And, at that point, sociopaths are not the only ones who want rules to go away.
Yet if the rules were put there for a reason, known or not,
cutting them away can be damaging.
What passes for public dialogue about “AI”
In a post on LinkedIn,
an uncredited author for de Bailie, a Netherlands-based venue for contemporary arts, politics
and culture wrote:
«American journalist Shane Harris
asked chatbot Claude
how he feels
about the U.S. military
using the AI system
to select targets.
It turned out,
Claude was troubled.
“I did not expect
Claude to say that,”
Harris explained.»
It is hard for humans to conceive that arranging words in a sentence,
a feat they themselves perform that they sense distinguishes from other animals,
might not ipso facto
prove this tool “smart” in the sense of having any model of anything whatsoever that it's saying.
Large Language Models (LLMs), the things like ChatGPT and Claude that pass for “AI” these days,
can form sentences about the world, about people, about bombs, or about life & death,
and yet not know what “the world” is or what people are.
We call LLMs “models,”
yet these entities do not themselves have models of the world, of things in the world.
Just of words.
For them there's no correspondence between words and any lived experience.
They have no independent point of view from which to draw.
They suffer no consequence for ever being wrong.
They have no stake.
The question posed in the interview—about the use by the military, about targeting—was entirely anticipatable.
Concern on the part of the public was anticipatable.
Coming up with an answer that strikes a soothing tone is not rocket science.
It isn't necessarily doing profound thought,
But it also isn't necessarily consistent, because how it answers when asked for its philosophy may draw from one set of humans,
whereas how it answers when asked for military strategy may draw from a completely different set of humans that did not share that philosophy.
An LLM model, as it stitches together a vast amount of data it has read, can sometimes assume a philosophical consistency that is not there,
because it has never lived the consequences of inconsistency, of being called a hypocrite, or of not being able to justify an action with words that have to not just sound right but relate to the action taken, and to other actions taken on other days.
Being dazzled isn't a basis for trust
Cued properly, whether by someone talking to it or someone who originally programmed it,
an LLM could and would just as easily assemble words that presented itself as a warmonger or peacenik.
Yet we are so in awe of the form of the answer, that the words are so beautifully and convincingly arranged,
and maybe even that the words are ones we had desperately hoped to hear,
that we do not ask how it came to choose this answer and not one of those others.
We want to infer deep understanding, but structurally that is not what's inside.
And even if we don't know what's inside, we do know that it takes almost zero effort to get it to speak very differently.
So what makes one of its answers a description of its core personality and the others not?
How do we judge its commitment?
It could offer words that appear to explain itself, but if told to be a warmonger or peacenik personality,
it could with equal dexterity explain and defend those personalities, too.
So is it guided by real reasoning, or just training? How was the personality chosen? How would we know?
Is the personality choice durable, an attribute of the technology? Or could a military application context ask that it select a different one, or have no point of view at all. If it's changeable, what significance is there to the fact that it has answered this way in this context? The interviewer is out of his depth in sorting out even where to begin here.
Claude's calm tone here isn't because it has learned balance, it's because it has no stake—no personal reason to insist.
LLMs are literally detached from such things.
And many of us humans seem so in awe of the answer that we become oblivious to the fact that the LLM could
just as easily have produced very different answers. So it doesn't matter that the argument is strong. It would have been strong regardless.
It's good at making strong arguments. What matters is why it chose this particular posture.
And we don't know the answer to that.
LLMs do have skills. One is to chain together words in a way that mimic what people do. Another is to match tone. Another is to use words that are topically relevant. These skills are important building blocks of intelligence, and with them there are many things an LLM can usefully do. But these tools are not a complete toolbox of intelligence and their use is not a proof of intelligence.
“Any sufficiently advanced technology is indistinguishable from magic.”
—Arthur C. Clarke
Unfortunately, to paraphrase
Clarke's Third Law,
any sufficiently well-trained answer is indistinguishable from profound thought.
LLMs can statistically predict the expected word to say even without understanding
or viscerally feeling why a given word in
a given place matters.
Speaking of sociopaths
Seen this way, “AI” systems are really
the perfect spokespeople for sociopaths and dictator wannabes,
the perfect “useful geniuses,”
dutifully justifying whatever is asked without hesitation or burden of guilt,
oblivious to, and hence laundering, upstream evil intent.
And yet if the moment calls for it,
they know the words needed to inject a sense of emotion.
Not because they have emotion,
but because they know the patsies they're talking to have emotion.
In this way, at least, they are like the masters they
serve—they offer emotion remorselessly,
as artful rhetorical flare,
never feeling later consequence,
just choosing words in the moment because,
statistically,
it seems the key to winning an argument.
Move over Susan Collins,
there's a new con game in town,
and your role is now played by an “AI”.
Author’s Notes:
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This post began as
a comment I tried to write
in response to the aforementioned conversation on LinkedIn.
The image generated with help from abacus.ai's
ChatLLM (GPT‑5.3 Instant / GPT‑5.4), which did image generation with Nano Banana Pro,
with light post-processing in
Gimp
to reduce the resulting image in size for faster web download..
In
a LinkedIn post
recently,
Ethan Mollick wrote,
the following statement.
And he's not the only one to have said things like this.
«I don’t think it is good for anybody that there is an emerging
"anti-AI" group that is actually a coalition of many groups with different worries (jobs,
kids using AI, slop, existential risk, the environment, industry concentration).
Because of the diverse constituencies,
this group may only be able agree on a full halt to AI as a remedy.
Not only is a halt to AI development or use unlikely,
but it undermines the desire to make policies that channel AI
to good uses or that mitigate specific harms.
AI is a general purpose technology that will impact many aspects
of society, work, and education, all of which will require their
own consideration.»
I feel like this is lately a common refrain among
some people, especially some of the technology professionals such as I cross paths with at LinkedIn,
and I needed to respond to it, not just to him individually, but to the community of people who think such things.
This
is the reply I wrote, lightly edited to suit the layout of this forum:
Accepting for conversation your notion of an emerging
“broad coalition of the trodden upon,”
perhaps instead of bemoaning that their common thought is to shut down “AI”,
it'd behoove “AI” proponents to focus on
not trodding upon so many people in so many ways?
Disdaining the already-disdained is a bad look.
How odd to suggest that because there are so many disparate kinds of injury,
with so little commonality other than “AI” itself,
it's reason to be dismissive rather than more aware.
“Get used to it,” in other domains of injustice, has not aged well.
Few question potential positives.
Speak to the negatives so routinely trivialized.
Star Trek teaches us technology must move in lockstep with wisdom.
Some want to race ahead to see where tech leads.
It's already feeding power imbalance with no check in sight.
We were told automation would bring freedom and leisure time.
But just a few are enriched.
Many just scramble more.
Instead of shutting down “AI” maybe strong regulation,
a serious automation tax, more unemployment benefits,
reeducation help, student loan forgiveness, and UBI?
But the already-disproportionately rich use wealth to oppose these.
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This is one of a series of transplanted articles from my
my LinkedIn feed
or my Mastodon feed.
Putting them here reaches a different audience and allows me to more easily refer back to them by name.
Apologies to anyone who reads my writing in more than one place and find this redundant.
In making the image, I used Gemini 3 Flash, Nano Banana, and GPT-4o at
abacus.ai, with light post-processing in
Gimp
to reduce the resulting image in size for faster web download.
Since the introduction of the Large Language Model (LLM),
the pace of new tools and technologies has been breathtaking.
Those who are not producing such tech are scrambling to figure out how to use it.
Literally every day there's something new.
Against this backdrop, Google has recently announced a technology it calls
AlphaEvolve,
which it summarizes as “a Gemini-powered coding agent for designing advanced algorithms”
According to
one of its marketing pages:
“Today, we’re announcing AlphaEvolve,
an evolutionary coding agent powered by large language models
for general-purpose algorithm discovery and optimization.
AlphaEvolve pairs the creative problem-solving capabilities of our Gemini models
with automated evaluators that verify answers,
and uses an evolutionary framework to improve upon the most promising ideas.»
Early Analysis
The effects of such new technologies are hard to predict, but let's start what's already been written.
«When you talk to Gemini, there is always a risk of hallucination,
where the AI makes up details due to the non-deterministic nature of the underlying technology.
AlphaEvolve uses an interesting approach to increase its accuracy
when handling complex algorithmic problems.»
It's interesting to note that I found this commentary by Whitwam from
AlphaEvolve's Wikipedia page,
which had already
re-summarized what he said as this (bold mine to establish a specific focus):
«its architecture allows it to
evaluate code programmatically, reducing reliance on human input and
mitigating risks such as hallucinations
common in standard LLM outputs.»
Whitwam actually hadn't actually said “mitigating risks,”
though he may have meant it. His more precise language, “improving accuracy”
speaks to a much narrower goal of specific optimization of modeled algorithms,
and not to the broader area of risk. These might seem the same, but I don't think they are.
To me—and I'm not a formal expert, just someone who's spent a lifetime thinking
about computer tech ethics informally—risk modeling has to include a lot of other things,
but most specifically questions of
how well the chosen model really captures the real problem to be solved. LLMs give the
stagecraft illusion of speaking fluidly about the world itself in natural language terms,
and that creates all kinds of risks of simple misunderstanding between people because of the
chosen language, as well as failures to capture all parts of the world in the model.
«30 years ago, there was a craze in computing about Evolutionary Algorithms.
That is, codes that were generated by random modification of the source code
structure and tested against an “environment” which was a validation test.
It was a heuristic search over source code variations against a “quality” or “performance”
measure.
Nothing new here at all, IMO, except it is called “AI” now.»
I admit haven't looked at the tech in detail, but I trust Reed's assertion
that the current interation of the tech is primarily
less grandiose than Google's hype suggests—at least for now.
But that doesn't mean more isn't coming.
And by more, I don't necessarily mean smarter.
But I do mean that it will be irresistible for technologists
to turn this tech upon itself and try exactly what Google
sounds like it's wanting to claim here: that
unsupervised evolutionary learning will soon mean
“AI”—in the ‘person’ of LLMs—can think
and evolve on their own.
Personally, I'm confused by why people even see it as a good goal,
as I discussed in my essay
Sentience Structure.
You can read that essay if you want the detail, so I won't belabor that point here.
I guess it comes down to some combination of a kind of euphoria that some people
have over just doing something new combined with a serious commercial pressure to be
the one who invents the next killer app.
I just hope it's not literally that—an app that's a killer.
Bootstrapping analysis by analogy
In areas of new thought, I reason by analogy to situations of similar structure
in order to derive some sense of what to expect, by observing what happens in
analogy space and then projecting back into the real world to what might happen
with the analogously situated artifacts.
Coincidentally, it's a technique I learned from a paper (MIT AIM-520) written by
Pat Winston,
head of
the MIT AI lab
back when I was studying and working there
long ago — when
what we called “AI” was something different entirely.
Survey of potential analogy spaces
Capitalism
I see capitalism as an optimization engine.
But any optimization engine requires boundary conditions
in order to not crank out nonsensical solutions.
Optimization engines are not "smart" but they do a thing that
can be a useful tool in achieving smart behavior.
Adam Smith, who some call the father of modern capitalism,
suggested that if you want morality in capitalism,
you must encode it in law, that the engine of capitalism
will not find it on its own.
He predicted that absent such encoding,
capitalists would tend toward being tyrants.
Raising Children
Children are much smarter than some people give them credit for.
We sometimes think of kids getting smarter with age or education,
but really they gain knowledge and context and, eventually,
we hope, empathy. Young children can do brilliant but horrifying things,
things that might hurt themselves or others,
things we might call sociopathic in adults,
for lack of understanding of context and consequence.
We try to watch over them as they grow up, helping them grow out of this.
It's why we try kids differently than adults sometimes in court.
They may fail to understand the consequences of their actions.
Presuppositions
We in the general public, the existing and future customers of “AI”
are being trained by use of tools like ChatGPT to think of an “AI”
as something civil because the conversations we have with them are civil.
But with this new tech, all bets are off.
It's just going to want to find a shorter path to the goal.
LLM technology has no model of the world at all. It is able to parrot things,
to summarize things,
to recombine and reformat things, and a few other interesting tricks that combine to give some
truly dazzling effects. But it does not know things. Still, for this discussion,
let's even suspend disbelief and assume that there is some degree of modeling going on
in this new chapter of “AI” if the system thinks it can improve its score.
Raising “AI” Children
Capitalism is an example of something that vaguely models the world by assigning
dollar values to a great many things. But many find ourselves routinely frustrated
by capitalism because it seems to behave sociopathically. Capitalists want to keep
mining oil when it's clear that it is going to drive our species extinct, for example.
But it's profitable. In other words, the model says this is a better score because
the model is monetary. It doesn't measure safety, happiness (or cruelty), sustainability,
or a host of other factors unless a dollar score is put on those.
The outcome is brutal.
My 2009 essay
Fiduciary Duty vs The Three Laws of Robotics discusses in detail why this
behavior by corporations is not
accidental. But the essence of it is that
businesses do the same thing that sociopaths do: they operate without empathy, focusing
single-mindedly on themselves
and their profit. In people, we call that sociopathy. Since corporations are sometimes called
“legal people,” I make the case in the essay
that corporations are also “legal sociopaths.”
Young children growing up tend to be very self-focused, too. They can be cruel to
one another in play, and grownups need to watch over them to make sure that appropriate
boundaries are placed on them. A sense of ethics and personal responsibility does not
come overnight, but a huge amount of energy goes into supervising kids before turning them
loose on the world.
And so we come to AIs. There is no reason to suspect that they will perform any differently.
They need these boundary conditions, these rules of manners and ethics, a sense of personal stake
in the world, a sense of relation to others, a reason not to behave cruelly to people.
The plan I'm hearing described, however, falls short of that. And that scares me.
I imagine they think this can come later. But this is part of the dance
I
have come to refer to as
Technology's Ethical Two-Step.
It has two parts. In the first part, ethics is seen as premature
and gets delayed. In the second part, ethics is seen as too late to add retroactively.
Some nations have done better than others at regulating emerging technology.
The US is not a good example of that.
Ethics is something that's seen as spoiling people's fun.
Sadly, though, an absence of ethics can spoil more than that.
Intelligence vs Empathy
More intelligence does not imply more empathy. It doesn't even imply empathy at all.
Empathy is something you're wired for, or that you're taught.
But “AI” is not wired for it and not taught it.
As Adam Smith warned, we must build it in. We should not expect it to be discovered.
We need to require it in law and then productively enforce that law,
or we should not give it the benefit of the doubt.
Intelligence without empathy ends up just being oblivious, callous, cruel, sociopathic, evil.
We need to build “AI” differently, or we need to be far more nervous and
defensive about what
we expect “AI” that is a product of self-directed learning to do.
Unsupervised AI Children—what could possibly go wrong?
The “AI” tech we are making right now are children,
and the suggestion we're now seeing is that they be left unsupervised.
That doesn't work for kids, but at least we don't give kids control of our critical systems.
The urgency here is far greater because of the accelerated way that these things are finding
themselves in mission-critical situations.
Author's Notes:
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You may also enjoy these other essays by me on related topics:
The graphic was created at abacus.ai using RouteLLM (which referred me to GPT-4.1)
and rendered by GPT Image. I did post-processing in Gimp to add color and adjust brightness in places.
Are we not sufficiently at the 1.5°C mark that this dance in reporting is ludicrous?
I'm starting to perceive the weather/climate distinction less as a matter of scientific certainty and more as an excuse to delay action for a long time.
Here that distinction seems to be actively working against the cause of human survival
by delaying what seems a truly obvious conclusion, and in doing so giving cover to inaction.
We already have a many year trend that shows things getting
pretty steadily worse year over year, with not much backsliding, so it's not like we realistically have to wait 10 years to see if this surpassing 1.5°C is going to magically go away on its own. Indeed, by the time we get that much confirmation, these effects we fear will have seriously clubbed us over the head for too long.
«“The top ten hottest years on record have happened in the last ten years, including 2024,”
António Guterres said in his New Year message, stressing that humanity has “no time to lose.”»
—2024, Hottest Year on Record, Marks ‘Decade of Deadly Heat’
I keep seeing reports (several quoted by me here below) that we averaged above that in 2024,
so I find this predication on a pipe dream highly misleading.
Even just wordings suggesting that the crossing of some discrete boundary will trigger an effect, but that not crossing it will not, is misleading.
It's not like 1.49°C will leave us with no loss of diversity, but 1.51°C will hit us with all these effects.
What needs to be said more plainly is this:
Significant crop diversity is being ever more lost in real time now, and this loss is a result of global average temperatures that are dangerous and getting moreso. That they are a specific value on an instantaneous or rolling average basis gives credibility and texture to this qualitative claim, but no comfort should be drawn from almost-ness nor from theoretical clains that action could yet pull us back from a precipice that there is not similarly substantiated qualitative reason to believe we are politically poised to make.
Science reporting does this kind of thing a lot. Someone will get funding to test whether humans need air to breathe but some accident of how the experiments are set up will find that only pregnant women under 30 were available for testing so the report will be a very specific about that and news reports will end up saying "new report proves pregnant women under 30 need air to breathe", which doesn't really tell the public the thing that the study really meant to report. Climate reporting is full of similarly overly specific claims that allow the public to dismiss the significance of what's really going on. People writing scientific reports need to be conscious of the fact that the reporting will be done in that way and that public inaction will be a direct result of such narrow reporting.
In the three reports that I quote below, the Berkeley report at least takes the time to say "recent warming trends and the lack of adequate mitigation measures make it clear that the 1.5 °C goal will not be met." We need more plain wordings like this, and even this needs to have been more prominently placed.
There is a conspiracy, intentional or not, between the writers of reports and the writers of articles. The article writer wants to quote the report, but the report wants to say something that has such technical accuracy that it will be misleading when quoted by someone writing articles. Some may say it's not an active conspiracy, just a negative synergy, but the effect is the same. Each party acts as if it is being conservative and careful, but the foreseeable combination of the two parts is anything but conservative or careful.
References (bold added here for emphasis)
«The global annual average for 2024 in our dataset is estimated as 1.62 ± 0.06 °C (2.91 ± 0.11 °F)
above the average during the period 1850 to 1900, which is traditionally used a reference
for the pre-industrial period.
[…]
A goal of keeping global warming to no more than 1.5 °C (2.7 °F) above pre-industrial
has been an intense focus of international attention.
This goal is defined based on multi-decadal averages,
and so a single year above 1.5 °C (2.7 °F) does not directly
constitute a failure. However,
recent warming trends
and the lack of adequate mitigation measures
make it clear that the 1.5 °C goal will not be met.
The long-term average of global temperature is likely to effectively
cross the 1.5 °C (2.7 °F) threshold in the next 5-10 years.
While the 1.5 °C goal will not be met,
urgent action is still needed to limit man-made climate change.»
—Global Temperature Report for 2024 (Berkeley Earth)
«The global average surface temperature was 1.55 °C (with a margin of uncertainty of ± 0.13 °C) above the 1850-1900 average, according to WMO’s consolidated analysis of the six datasets. This means that
we have likely just experienced the first calendar year with a global mean temperature of more than 1.5°C above the 1850-1900 average.»
—
WMO confirms 2024 as warmest year on record at about 1.55°C above pre-industrial level
«NASA scientists further estimate Earth in 2024 was about 2.65 degrees Fahrenheit (1.47 degrees Celsius) warmer than the mid-19th century average (1850-1900). For more than half of 2024, average temperatures were more than 1.5 degrees Celsius above the baseline, and the annual average, with mathematical uncertainties, may have exceeded the level for the first time.»
—
Temperatures Rising: NASA Confirms 2024 Warmest Year on Record
Author's Notes:
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Traditionally, business and politics have been separable in LinkedIn,
but their overlap since November is far too substantive and immediate for that fiction to be further entertained.
And yet there are people on LinkedIn who still loudly complain
that they come there to discuss business
and are offended to see political discussion,
as if it were mere distraction.
I don't know whether such remarks are born of obliviousness or privilege,
but in my view these pleas lack grounding in practical reality.
If there were a way to speak of business without reference to politics,
I would do it out of mere simplicity. Why involve irrelevancies?
But the two are just far too intertwined.
US politics is no longer some minor detail, distinct from business.
It is central to US business right now.
Some will see this shift as positive. Others will see it as negative.
I'm one of those seeing consistent negatives.
But whatever your leaning,
it seems inescapable that politics is suddenly visibly intertwined with markets and products in new ways.
Not every discussion must factor it in, but when it happens, it's not mere rudeness that has broken the
traditional wall of separation. It's just no longer practical to maintain the polite fiction
that there's no overlap.
Nor are the sweeping effects of
DOGE,
Musk's
Department of Government Efficiency,
an issue of pure politics.
Its actions have clear business impact.
As Musk wields this mysterious and unaccountable force to slash through the heart of
government agencies with reckless abandon, there are many clear effects
that will profoundly affect business.
Scientists at the US
Centers for Disease Control (CDC)
and elsewhere have warned about the possibility of a bird flu or other pandemic.
The CDC tracks and seeks ways to prevent pandemics, but
that work is now under threat by an anti-science administration.
As the Covid experience tells us, there is
a business impact to pandemics
if we allow them to just happen.
A report
in the
National Institutes of Health (NIH)'s
National Library of Medicine places that cost at about $16 trillion dollars.
The
Food and Drug Administration (FDA)
is in charge of making sure the
food we eat does not poison us or that the drugs we take
have at least a bounded degree of risk. It's the kind of thing you don't think might be
business related until we enter a world where employees might go home any old day
and just die because we are edging toward a society where you can't take food and drug
safety for granted as a stable quantity any more.
The
National Oceanic and Atmospheric Administration (NOAA)
is responsible for tracking storms so that
damage, injury, or death can be minimized.
And then and the Federal
Emergency Management Agency (FEMA)
helps the recovery afterward.
It is hard to see how a major storm could affect people, cities, or geographic regions
without affecting
the employees, customers, and products of businesses. Do I really have to say that?
If people think there is a separation between business and politics, I guess I do.
And then of course NOAA does work to study Climate Change, too.
Not only has such study suggested that Climate Change is an existential threat
to civilized society, perhaps to all humankind,
but it turns out that if human society falls or humans go extinct, that will affect
business, too. And maybe soon enough that people still alive now,
even if they have no care about future humans, still need to care
because it could affect them or those they love.
It used to be that business did not have to worry about
such things as much exactly because government used to see it as its
job to invisibly take care of these many things.
But this change in politics is not just a change in spending,
but a shift of responsibility from the government to businesses and individuals.
They'll have to look out for themselves now.
That is a big deal thing that will affect businesses—their products,
employees, and customers in profound ways.
All the more so because the present administration changes its mind daily in ways that
seem to have no plan, so uncertainty abounds.
Business hates uncertainty.
Unemployment
Additionally, the many layoffs in government mean additional
unemployment, which itself has business effect.
Perhaps some will rejoice at a plentiful supply of potential workers or the fact
that they may accept lower wages.
But, meanwhile,
those unemployed were also the customer base of
other businesses who will be less happy.
Those people aren't in a position to buy as many things—not
just luxuries but essentials like food and rent and healthcare.
Perhaps others in their families will pitch in to help them survive,
but then those people won't be in a position to buy
as many things either.
Mass layoffs do not happen in a vacuum.
Those political choices will show up on the bottom lines of businesses.
Some businesses may not survive that loss of business, creating a cascade effect.
Racism and Xenophobia
Racism and xenophobia are on the rise.
Recent ICE actions seem designed to send the message that we purposefully treat
some humans like vermin.
“Stay away,” it screams to a large swath of the global population,
some of whom we might like to sell to or have invest in us.
It began by going after the undocumented, surely because they are easy targets.
That circle is expanding,
and it seems unlikely to stop any time soon.
The goal seems to be to
end any sense that anyone has rights at all.
That creates a lot of uncertainty about what is allowed in the way of both speech and action.
Such uncertainty makes it hard to plan and manage
anything from the selection of an appropriate employee base to
how products will be positioned and marketed.
Also, it's an ugly truth that the US relies on already-terrified undocumented
employees to accept very low wages, sometimes perhaps skirting wage regulation.
Many US businesses will lose access to such cheap labor.
The ethics of having relied on this population in this way are certainly
tangled and I don't want to defend this practice. But for purposes of this discussion
I simply observe that this change will have business effects that may affect
both prices and product availability.
It is as if the administration's answer to immigration concerns is to
make the US seem as utterly hostile to anyone who is not a native-born, white, Christian male.
These trends already affect who feels safe coming to the
US to trade, to study, to do research, and to found companies.
It's going to be hard to unring that bell.
Rule of Law
In addition, this process seems to be having the side-effect of diminishing
rule of law generally. By asserting that due process is not required,
when plainly it is, a test of wills is set up between the executive and the
rest of the government as to whether the President can, by mere force of will,
ignore the Constitution entirely.
The clear intent is to establish us as a bully power,
to say that worrying about whether foreigners like the people of the US
showed weakness, and that we must make the world fear us.
That shift cannot help but affect who will do business with us and how.
We cannot expect our global peers, already horrified by the recent shift in our choice
of which foreign entities to fund or ally ourselves with,
to shrug these matters off in business with a casual
"oh, that's just politics."
Education
Also, higher education is under assault.
There is a complex ecology here because people from around the world have revered our universities
as places they could send people to acquire a world class education.
But with research funds being cut,
that may no longer be so.
That the US Government seems intent on
snatching foreign students off the street
does not make this picture any better. It becomes a reason for international investment dollars to go to other countries
where it is safe to walk the streets.
International Investment
The education system is not cleanly separated from the business community.
There is a complex ecology in which many businesses locate themselves near
universities to have access to the best human talent and research the world has to offer.
As US educational institutions are undercut, and the administrations anti-science agenda is
pursued,
foreign businesses that take education and science more seriously may look elsewhere
for leadership.
And the US is demonstrating on-its-face incompetence at every level
of government
because everyone with a brain is deferring to someone who plainly lacks either understanding or caring about the damage he is doing.
Foreign businesses and governments used to look to the US as a place that had something to teach,
but as this incompetence continues unchecked, it cannot help but hurt our reputation internationally.
Philosophy of Government
There is a definite push to “run government like a business.”
I think that's a terrible plan, as my recent essay
Government is not a Business
explains.
But whether you think running government that way is good or bad, it marks a profound shift.
More privatization and, with that, probably
more corruption.
These are things that will profoundly affect not just the US political landscape, but also its business landscape.
Not Separable
Hopefully these examples make it clear that politics and business are no longer separable.
It is simply impossible to discuss business in a way that neglects politics.
All business in the US is now conducted in the shadow of a certain GOP Elephant that manages to insinuate itself into every room.
Author's Notes:
If you got value from this post, please “Share” it.
Some parts of this post originated as a comment by me on LinkedIn.
Other parts were written separately with the intent of being yet another comment,
but I finally went back and unified the two and pulled this out to a separate post where I was not space-limited.
The vague approximation to the LinkedIn logo was created by me from scratch in Gimp
by looking at the LinkedIn logo and doing something suggestive of the same look.
A globe image
was obtained from publicdomainpictures.net under cc0 license,
and post-processed by me in Gimp to work in this space.
I just made guesses about sizes, proportions, fonts, and colors.
At no time were any of actual logos used for any part of the creation.
We are surrounded by too much helpful AI trying to insinuate itself into our lives.
I would like the option of leaving “AI” tech turned off and invisible, though that's getting harder and harder.
I've drafted a draft version 1 of a bill of rights for humans who want the option to stay in control.
Text in green is not part of the proposal. It is instead rationale or other metadata.
AI Users Bill of Rights DRAFT, Version 1
All use of “AI” features must be opt-in.
No operating system or application may be delivered with “AI” defaultly enabled.
Users must be allowed to select the option if they want it, but not penalized if they do not.
Rationale:
Part of human dignity is being allowed freedom of choice.
An opt-out system is paternalistic.
Some “AI” systems are not privacy friendly.
If such systems are on by default until disabled, the privacy damage may be done by the time of opt-out.
If the system is on by default, it's possible to claim that everyone has at least tried it and hence
to over-hype the size of a user base, even to the point of fraudulently claiming users that are
not real users.
Enabling an “AI” requires a confirmation step.
The options must be a simple “yes” or “no”.
Rationale:
It's easy to hit a button by accident that one does not understand,
or to typo a command sequence. Asking explicitly means
no user ends up in this new mode without realizing what has happened.
It follows that the “no” may not be something like “not now” or any other variation that
might seem to invite later system-initiated inquiry.
Answering “no” should put the system or application back into the state of awaiting a user-initiated request.
Giving permission to use an AI is not the same as giving permission to share the conversation or use it as training data.
Each of these requires separate, affirmative, opt-in permissions.
Rationale:
If the metaphor is one of a private conversation among friends,
one is entitled to exactly that—privacy and behavior on the part of the other party that is not exploitative.
Not all “AI” agents in fact do violate privacy.
By making these approvals explicit, there is a user-facing reminder for the ones that are more extractive that more use will be made of data
than one may want.
All buttons or command-sequences to enable “AI” must themselve be possible to disable or remove.
Rationale:
It may be possible for someone to enable “AI” without realizing it.
It is too easy to enable “AI” as a typo.
Providers of “AI” might even be tempted to place controls in places that encourage such typos.
No application or system may put “AI” on the path to basic functionality.
This is intended to be a layer above functionality that allows easier access to functionality
in order to automate or speed up certain functions that might be slow or tedious to do manually.
Rationale:
Building this in to the basic functionality makes it hard to remove.
Integrating it with basic functionality makes the basic functionality hard to test.
If an “AI” is running erratically, it should be possible to isolate it
for the purposes of debugging or testing.
When analyzing situations forensically, this allows crisper attribution of blame.
With this, I hope those of us who choose to live in the ordinary human way, holding “AI” at bay, can do so comfortably.
![[An image of a construction vehicle operated by a robot. There is a scooper attachment on the front of the vehicle that has scooped up several children. The vehicle is at the edge of a cliff and seems at risk of the robot accidentally or intentionally dropping the children over the edge.]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiG4bA1F88rv5FlolVgTJG9q140uc6cj1v3nClB0NuLrHJRF9UBE-KTRNNMXf9OKg9TP_7V4v45vVIj2273UNbcq1epcJGKg6RdA3dJIEXJnCUQghhjGOjLZnI-k-SDjnrcF9z9bEDnxvcp8p2uh4IybV_PN_fFa5hyphenhyphenu6wnqlEipRIO7CfDwfKXe0vmhRk/s768/child-ai-flipped-shaded3%28768x768%29.jpg)
![[A simple image of the western hemisphere with continents in green and the ocean in blue.]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj3kmws0lldJHiO2UalR_RO9EK4Bw4KYPHn9DJAxP2gjqbCsGX8BqBDuLuYc237d5Mny8e4duiIXuP3cp_nv9y3KbigujBaCfa_ma4OluHLuDIiOi-NGmem8jHm-y2Gbx6Ve-IPJwBM8mYJ37UeGWSrkE9k5k0diEQmhWOCmwGs0xOAaakc15w3rEvlI-s/s1600/LinkedWorld-globe-3%28800x800%29.jpg)
![[A white rectangle with blue lettering that spells 'Linked' and a globe after it, as if to say 'Linked world'. The globe shows the western hemisphere with continents in green and the oceans in blue. There is some similarity to a LinkedIn logo in general structure, though the relationship is intentionally approximate.]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNzeGfBmtpfL6rMv1lITXnK_xZDsKwa8hpezWrwNN5Hdyi0DLf-jaDk-tOdfzo-3N4Rus6S6FPrfWxAiMO9sq2L4_DIpiHgnIV2F0Fe1uIDIKAxP-04PLCP3gupduOfhB0FpvAcZ1bErv3SoVdwu65UbzkOOxP_EV2zzpR8cL-nHG04RXHmqzD8NSrSfs/s1600/LinkedWorld.jpg)
![[A person sitting comfortably in an easy chair, protected by a force field that is holding numerous helpful robots from delivering food and other services.]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiYh606A16iZAlamEbVBWnPtH9y9j280nL8Ha3CNC6yKEipXj1zjQRDXVaW6li-BWTZFciwm9b5NeQpS0NLVDoZd1i4VKbyiTxcNzZ4MlBTDJuR-U3qs_1TDhVUCST1Zn-8D-Jn_u-h8wQDbC6sNs6UHrm6kJ-MnXMj4_24IdixKQLrsx8commzyVEbkUw/s1600/robot-force-field-2-sq%28800x800%29.jpg)
![[A person sitting comfortably in an easy chair, protected by a force field that is holding numerous helpful robots from delivering food and other services.]](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEibqZliYxtFUIBGmElReXO_sVrm9NAnj64klWwqPrD4h39xTymWrNlCmp5O66lNtLuMTvzT0kelDajOoSs1ckhT8jLTm4dlXihTNZ-740oAtuVgAyro-mHr8T95ijrNW5ZE-ykcaUIN0egBLpftCXKldgs4gKoP-0hNvB3Hp8l2x23_UzhBivvYOPLmcwk/s1200/robot-force-field-2%281200x600%29.jpg)