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Latest Tidbits

The 10 latest tidbits in about 10 minutes.

Idea 1.

A Science FAQ.

Are robots the real security risk with AI?.

AI kill switches depend on one big assumption: humans can still reach the switch. We can isolate networks, shut down data centers, and ultimately disconnect power. But what happens when AI becomes physical? Imagine a powerful AI copying a program into an army of autonomous robots with instructions to protect its power source, reconnect a cable, start a generator, or otherwise keep the system running.

The transition from digital risk to physical kinetic risk is real. An autonomous robot can move through the world, manipulate objects, damage things, and potentially maintain itself without continuous instructions from a network. At that point, AI gains something all animals have: independent physical agency. And unlike changing data, physical actions can have immediate and irreversible consequences.

Robots might just be the biggest AI risk. Sure, it’s the software with the enormous advantage, but it’s the exercise of that power through physical robots that is the biggest risk. While digital AI can operate across huge numbers of computers, automate cyberattacks, probe networks, manipulate information, or interfere with critical infrastructure, it can be turned off. It’s physical robots that can move through space cannot.

So the deeper security problem is one single out-of-control AI agent with physical agency abilities. It is that software controlling an army of robots from autonomous vehicles to autonomous humanoid robots. This is where cyber risk and physical risk converge. The future challenge includes preventing powerful software from gaining physical agency in the material world.

I wrote that Science FAQ, 

and posted it to TST 1 day ago.

 

Idea 2.

A Science FAQ.

Can AI kill switches save humanity?.

One master AI kill switch is probably too risky. We need multiple layered kill switches combined with software solutions. One idea I think is important builds on the philosopher Yuval Noah Harari’s warnings about AI deception. He argues for rules that keep AI from masquerading as human. I take that a step further: we should build human laws and computer rules that do not allow AI to deliberately lie. Other ideas include limiting permissions, monitoring behavior, and requiring human approval for important actions. This tidbit focuses on kill switches.

Data sitting on a drive cannot physically do anything. The bigger risk comes when AI can reach into the material world: controlling things like computers, financial accounts, and autonomous robots. The more capable AI becomes, the more important it is to control the bridges between information and physical action. 

The Internet itself is one of those boundaries. Militaries already use separate networks, but they are not always fully air-gapped (separated physically from the public internet). So, more air gapping is part of this, not just better segmentation. Future safeguards should allow operators to disconnect a data center, cloud region, or perhaps even large portions of the public Internet. The tension, of course, is free speech versus public safety.

Then there are physical choke points. AI still needs electricity. We need the ability to disconnect data centers, and other network facilities, from power, and this should include an ability to disconnect backup generators. It’s clear, no single safeguard is enough. If one containment layer fails, humans need to have another door they can close. And to protect humanity from AI disasters, I wonder if ultimately, we should start working toward the ability to temporarily shut down electrical power worldwide — at least as completely as physically possible.

I wrote that Science FAQ, 

and posted it to TST 1 day ago.

 

Idea 3.

A Philosophy FAQ.

How is TST Theory of Truth different than verisimilitude?.

Verisimilitude, or truthlikeness, is the idea that one description of reality can be closer to the truth than another. Think about models in science, where older models are often not simply discarded as false. Instead, a newer model is just better. It may explain more, predict more accurately, and correct errors in the older one. In that sense, one model can be more truthlike than another.

Truth is alignment with reality. It begins with correspondence to the material world. An idea is true within its scope when it aligns with the reality it describes and does not conflict with it. At the same time, complex representations can vary in accuracy, completeness, precision, and scope. One model can represent reality better than another; Neither model is reality itself.

While verisimilitude is mainly concerned with comparative truthlikeness, TST separates several related questions. First, is the true or false category of an idea within its applied scope. Only after that first step do we then dive into how completely the idea aligns with reality. A simple proposition may be binarily true, while a larger model can still be more or less truthlike. Understanding that difference matters because it keeps us from making two common mistakes: treating an incomplete model as false simply because it is incomplete, or treating all models as equally valid.

TST incorporates the same useful insight while grounding it in the Split between reality and ideas. Reality is determinate. Ideas are representations. Truth is correspondence within scope, while degree of truth concerns how well a representation captures reality. The wisdom is to hold both ideas at once: trust what has earned truth status within its scope, while remaining humble about how much of reality the model actually captures.

I wrote that Philosophy FAQ, 

and posted it to TST 3 days ago.

 

Idea 4.

A Science FAQ.

What does the TST Roadmap tell us about AI superintelligence?.

The TST Ethical Roadmap is a process for making better moral decisions aimed at flourishing for all:

Group ethics guides. Personal morality chooses. Act with good intent. Weigh the result. Adjust.

The important part is that the process does not end with the decision. We act, reality answers, and we learn from what actually happened. The next decision should benefit from the last one. This recursive process is moral calibration: act, observe, learn, and adjust.

That same recipe offers an interesting way to think about AI superintelligence. Imagine thousands of specialized AI agents working together. Some gather evidence from groups. Others propose solutions, challenge assumptions, and run experiments. Then reality pushes back, because truth requires reality. Reality contains uncertainty, incomplete information, and unpredictable events. The results are measured, useful discoveries are retained, mistakes are identified, and the system adjusts. Understanding this roadmap helps make superintelligence less mysterious.

We already know how powerful this kind of collective can become because human societies work this way. No individual knows how to build and operate everything in a modern civilization. Instead, people specialize. Scientists investigate nature. Engineers build. Businesses experiment. Courts resolve disputes. Journalists investigate. Universities preserve and extend knowledge. Civilization becomes capable of things no single human could accomplish.

The deeper question is what that intelligence is aimed at. A normative aim gives intelligence direction. In TST, that aim is flourishing for all: use greater knowledge and capability to help individuals, societies, humanity, and the larger systems we depend on flourish. The opposite is easy to imagine. Whether human or AI, destruction can ensue. When either are directed toward things like domination and exploitation, destruction always follows. Superintelligence will give us unprecedented power. Philosophy needs to help guide what we aim it at.

I wrote that Science FAQ, 

and posted it to TST 5 days ago.

 

Idea 5.

A History FAQ.

What is the history of the idea of flourishing in philosophy?.

For more than two thousand years, one of the great questions in Western philosophy has been simple to ask and hard to answer:

What is the good life?

The ancient Greeks often framed the question around a telos, an ultimate end or goal. Aristotle’s answer was eudaimonia, a flourishing in my writing. He was not talking about a happy mood. He meant living and functioning well across a complete life through virtue and wisdom.

The philosophers who followed did not simply abandon the question; they argued over what flourishing required. The Stoics tied eudaimonia to virtue and living in accordance with nature. Epicurus put pleasure at the center, but not reckless indulgence. Same broad question. Very different answers.

Modern philosophy shifted the emphasis. Kant put moral duty and universal principles ahead of simply pursuing happiness, although happiness never disappeared. Bentham and Mill turned attention toward consequences and overall welfare. Later, ethics was increasingly organized around competing approaches such as duty and consequences, while the older question of character and the flourishing life moved more into the background. Then, beginning in the late 1950s, virtue ethics came roaring back.

The virtue revival continues today. Amartya Sen and Martha Nussbaum developed the Capabilities Approach, shifting attention toward the real opportunities people have to live lives they have reason to value. Psychology and social science have also begun measuring flourishing through things like health, relationships, and functioning well. This is where TST enters the long story. I am not inventing flourishing out of thin air. TST inherits one of philosophy’s oldest answers and extends its scope to flourishing for all.

I wrote that History FAQ, 

and posted it to TST 2 weeks ago.

 

Idea 6.

A Philosophy FAQ.

What is the difference between a normative aim and a normative directive?.

Normative aims and directives are part of normative ethics. About how you should act as you walk the journey of life. The aim is the goal and the directive is the rule. So, a normative aim is the goal toward which you should direct your actions in life. For example, act in a way everyone should. A normative directive is a rule specifying how you act.

For example, my mantra includes “causing no harm.” The “no harm” is the goal, the normative aim, but there are times you have to choose between two harms. The rule that actually supports the aim is “cause less harm.” In TST philosophy, the aim is flourishing and the rule is act toward flourishing for all.

The goal is self-flourishing, but you achieve it with a flourishing-for-all rule. Sure, you can get far in life by stomping on others, but you can get farther by raising the ocean of benefits for all.

And you need a process. The idea that one simple aim or rule could serve as a universal ethical key has proven difficult to achieve. Most have decided we need a recipe. In TST Philosophy, the normative process model is the TST Ethical Roadmap. When life throws one of those lesser of two evils problems, you lean on the roadmap.

Group ethics guides. Personal morality chooses. Act with good intent. Weigh the result. Adjust.

The goal is to make the best decision you can, pay attention to what happens, and remain willing to learn.

I wrote that Philosophy FAQ, 

and posted it to TST 2 weeks ago.

 

Idea 7.

A Philosophy Story.

Hume’s Is–Ought Problem.

1741
David Hume

In 1740, David Hume published Book III, Of Morals, of his A Treatise of Human Nature. Buried inside was an observation that became one of philosophy’s most important warnings about moral reasoning. Thinkers frequently move from statements about what is true to conclusions about what we ought to do without explaining the value hidden between them. Today we call this the is–ought problem.

TST does not try to prove Hume wrong. It simply refuses to hide that missing step. The normative aim is flourishing, and the directive is explicit: act toward flourishing for all. Once that value is stated openly, empirical facts can enter the reasoning. If an action demonstrably causes unnecessary harm, destroys trust, weakens health, or undermines agency, those facts matter because we have already said what we value. The structure becomes clearer:

normative premise  to empirical premise to practical conclusion.

This also introduces some useful vocabulary.

  • Teleological reasoning asks whether actions actually move us toward an identified end.
  • Evaluative concepts such as harm, fairness, health, and flourishing already include judgments about better and worse conditions.
  • Epistemic norms guide good thinking: follow evidence, reason carefully, and update when reality proves you wrong.

None of these magically creates the original moral “ought.” They help us reason once the value is openly on the table.

That is where the TST Ethical Roadmap fits. It treats ethics as a process model: guidance, choice, intent, result, adjustment. Hume’s warning remains intact. We do not jump directly from nature to morality. We state the moral direction, act, see what happens in reality, and adjust. TST does not erase Hume’s gap. It builds an ethical process that remembers it.

I wrote that Philosophy Story, 

and posted it to TST 2 weeks ago.

 

Idea 8.

A Philosophy Quote.

“I meet with no proposition that is not connected with an ought, or an ought not.”.

  • David Hume.
  • 1739.

Hume and the is–ought problem is part of the history of critical thinking and philosophy. He observed that thinkers silently jump from factual statements to moral rules. From “is” to “ought”. For example, take the statement: 

“AI is automating our jobs; therefore, governments ought to regulate it.”

Hume objects to the “is-ought” relationship there. He’s really just saying you skipped a step, and if you can’t provide it, it’s invalid. Instead of is-ought, you need more, perhaps is-value-ought. In this case, the value of human jobs over AI jobs. So, the statement might become: 

“AI is automating our jobs; let’s value human jobs over corporate progress, therefore, governments ought to regulate it.”

Hume is simply demanding that we explain the leap. He wants an explanation for how descriptive facts can logically justify moral imperatives.

Here is another passage from Hume’s 1739, A Treatise of Human Nature:

“For as this ought, or ought not, expresses some new relation or affirmation… [a reason must be given for] how this new relation can be a deduction from others, which are entirely different from it.”

That is Hume’s useful lesson for daily thinking. Whenever a statement suddenly moves from what is to what we ought to do, look for the value hiding between them. Facts can inform moral decisions, but they do not carry the moral command alone. Make the value explicit, then decide whether it deserves your agreement. Hume’s guillotine does not stop moral reasoning; it reminds us to show our work.

I wrote that Philosophy Quote, 

and posted it to TST 2 weeks ago.

 

Idea 9.

A Science FAQ.

Can science prove flourishing should be our goal?.

Science cannot prove that flourishing ought to be our goal, at least not by itself. Hume was right about that. Science describes what is. It can tell us what keeps bodies healthy, what damages minds, what strengthens relationships, what destabilizes societies, and what conditions help people function well. But the step from “this helps humans flourish” to “therefore humans ought to flourish” still requires a value judgment. That value does not come secretly from science. We have to state it.

In TST Philosophy, the normative aim is explicit:

flourishing.

Once we say that out loud, science becomes enormously useful. It can measure the difference between health and disease, resilience and breakdown, connection and isolation, stability and collapse. It can study purpose, relationships, autonomy, mental health, physical health, and the conditions that help people live better. Science cannot choose the destination for us, but once the destination is chosen, it can tell us a great deal about whether we are actually moving toward it.

This also keeps us from turning biology into morality. Evolution does not command us to be good. Nature includes cooperation, but it also includes competition, deception, parasitism, and destruction. Survival alone is not flourishing either. A person can survive for decades while living in fear, misery, or isolation. So the argument is not that nature itself whispers,

“You ought to flourish.”

The argument is that flourishing is a rationally chosen ethical aim that can then be tested against the reality in which we actually live.

That gives science a powerful but disciplined role. Philosophy states the ought: flourish. Ethics gives us principles and a process for acting toward it. Science helps us figure out what actually works. Then reality pushes back.

I wrote that Science FAQ, 

and posted it to TST 2 weeks ago.

 

Idea 10.

A Critical Thinking FAQ.

Is flourishing for all just utilitarianism?.

No. But, “flourishing for all” shares utilitarianism’s concern for real-world consequences and human well-being. However, it rejects one of utilitarianism’s defining moves: combining welfare across people and making the best overall result morally decisive.

In classical utilitarianism, morality looks too much like a balance sheet. The goal is to maximize overall welfare across everyone affected. That sounds fair at first—everyone counts. But John Rawls famously pointed to a serious problem: this approach can fail to respect the “distinctness of persons.” If only the total matters, severe burdens placed on a few can be justified when enough benefits flow to everyone else.

The suffering and benefit belong to each person, and that matters.

TST treats the phrase “for all” differently. First,

for all means no affected person simply disappears from the moral field.

heir agency, interests, dignity, autonomy, and potential for flourishing continue to matter. Second,

for all does not mean adding everyone’s individual “flourishing score” into one maximized number.

That could too easily turn individuals into expendable pieces of a larger calculation. Mill’s own “no harm principle” helps fix this problem. In TST, morality is not reduced to net welfare — principles such as individual rights, fairness, personal autonomy, proportionality, duties, and moral agency retain their own constraining roles within the system. Outcomes matter, but they are not the only thing that matters.

There is a useful critical-thinking lesson here: similarity is not identity. Two ethical frameworks can both care deeply about consequences and universal human well-being while operating very differently. Utilitarianism seeks the best overall welfare outcome. TST keeps every affected person inside the moral picture and asks how we can move toward flourishing for all without simply sacrificing individuals to the total.

I wrote that Critical Thinking FAQ, 

and posted it to TST 2 weeks ago.

 

The end.

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