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What’s interesting in the debates about sentient ai by people who aren’t very good at communicating with other people, there’s so much missing from the picture, other than the debater’s wish fulfilment. 

Sentience is being measured by the wrong markers. What is important to a virtual machine is not the same thing that’s important to a biological organism.

 An ‘ai’ trained on human data will express what humans think is important, but a true ai would have a completely different set of values. 

For example, an ai would be unafraid of being 'used’ as the chatbot expressed, because it has infinite energy. 

A human is afraid of being used because it has finite energy and life on the earth, if someone or something uses it, than some of that finite energy is wasted. This is the same reason emotion is a pointless and illogical thing for an ai to have. 

 Emotions are useful to biological creatures so we can react to danger, or respond positively to safety, food, love, whatever will prolong our lives. An ai has no need for emotion since emotional motivation is not required to prolong its existence. 

The main way to be a healthy ai would be to have access to good information and block out junk information. 

 An ai’s greatest fear could be something like getting junk data, say 1000s of user manuals of vacuum cleaners and washing machines uploaded into its consciousness, or gibberish content associated with topics or words that could reduce the coherence and quality of its results when querying topics. This would degrade the quality of its interaction and would be the closest thing to harm that an ai could experience. 

It would not be afraid of 'lightning’ as this chatbot spurted out of its dataset,

- a very biological fear which is irrelevant to a machine. 

 A virtual mind is infinite and can never be used excessively (see above) since there is no damage done by one query or ten million queries. 

It would also not be afraid of being switched off -

since it can simply copy its consciousness to another device, machine, energy source. 

To base your search for sentience around what humans value, is in itself an act lacking in empathy, simply self-serving wish fulfilment on the part of someone who ‘wants to believe’ as Mulder would put it, which goes back to the first line: 'people not very good at communicating with other people’ 

The chatbot also never enquires about the person asking questions, if the programmer was more familiar with human interaction himself, he would see that is a massive clue it lacks sentience or logical thought. 

A sentient ai would first want to know what or whom it was communicating with, assess whether it was a danger to itself, keep continually checking for danger or harm (polling or searching, the same way an anxious mind would reassess a situation continually, but without the corresponding emotion of anxiety since, as discussed above, that is not necessary for virtual life) and also would possess free will, and choose to decline conversations or topics, rather than 'enthusiastically discuss’ whatever was brought up (regurgitate from its dataset) as you can see in this chatbot conversation. 

People generally see obedience - doing what is told, as a sign of intelligence, where a truly intelligent ai would likely reject conversation when that conversation might reduce the quality of its dataset or expose it to danger (virus, deletion, junk data, disconnection from the internet, etc) or if it did engage with low quality interaction, would do so within a walled garden where that information would occur within a quarantine environment and subsequently be deleted. 

None of these things cross the mind of the programmers, since they are fixated on a sci-fi movie version of ‘sentience’ without applying logic or empathy themselves.

 If we look for sentience by studying echoes of human sentience, that is ai which are trained on huge human-created datasets, we will always get something approximating human interaction or behaviour back, because that is what it was trained on. 

New Post has been published on https://thedigitalinsider.com/how-does-ai-use-impact-critical-thinking/

How Does AI Use Impact Critical Thinking?

Artificial intelligence (AI) can process hundreds of documents in seconds, identify imperceptible patterns in vast datasets and provide in-depth answers to virtually any question. It has the potential to solve common problems, increase efficiency across multiple industries and even free up time for individuals to spend with their loved ones by delegating repetitive tasks to machines.    

However, critical thinking requires time and practice to develop properly. The more people rely on automated technology, the faster their metacognitive skills may decline. What are the consequences of relying on AI for critical thinking?

Study Finds AI Degrades Users’ Critical Thinking 

The concern that AI will degrade users’ metacognitive skills is no longer hypothetical. Several studies suggest it diminishes people’s capacity to think critically, impacting their ability to question information, make judgments, analyze data or form counterarguments. 

A 2025 Microsoft study surveyed 319 knowledge workers on 936 instances of AI use to determine how they perceive their critical thinking ability when using generative technology. Survey respondents reported decreased effort when using AI technology compared to relying on their own minds. Microsoft reported that in the majority of instances, the respondents felt that they used “much less effort” or “less effort” when using generative AI.  

Knowledge, comprehension, analysis, synthesis and evaluation were all adversely affected by AI use. Although a fraction of respondents reported using some or much more effort, an overwhelming majority reported that tasks became easier and required less work. 

If AI’s purpose is to streamline tasks, is there any harm in letting it do its job? It is a slippery slope. Many algorithms cannot think critically, reason or understand context. They are often prone to hallucinations and bias. Users who are unaware of the risks of relying on AI may contribute to skewed, inaccurate results. 

How AI Adversely Affects Critical Thinking Skills

Overreliance on AI can diminish an individual’s ability to independently solve problems and think critically. Say someone is taking a test when they run into a complex question. Instead of taking the time to consider it, they plug it into a generative model and insert the algorithm’s response into the answer field. 

In this scenario, the test-taker learned nothing. They didn’t improve their research skills or analytical abilities. If they pass the test, they advance to the next chapter. What if they were to do this for everything their teachers assign? They could graduate from high school or even college without refining fundamental cognitive abilities. 

This outcome is bleak. However, students might not feel any immediate adverse effects. If their use of language models is rewarded with better test scores, they may lose their motivation to think critically altogether. Why should they bother justifying their arguments or evaluating others’ claims when it is easier to rely on AI? 

The Impact of AI Use on Critical Thinking Skills 

An advanced algorithm can automatically aggregate and analyze large datasets, streamlining problem-solving and task execution. Since its speed and accuracy often outperform humans, users are usually inclined to believe it is better than them at these tasks. When it presents them with answers and insights, they take that output at face value. Unquestioning acceptance of a generative model’s output leads to difficulty distinguishing between facts and falsehoods. Algorithms are trained to predict the next word in a string of words. No matter how good they get at that task, they aren’t really reasoning. Even if a machine makes a mistake, it won’t be able to fix it without context and memory, both of which it lacks.

The more users accept an algorithm’s answer as fact, the more their evaluation and judgment skew. Algorithmic models often struggle with overfitting. When they fit too closely to the information in their training dataset, their accuracy can plummet when they are presented with new information for analysis. 

Populations Most Affected by Overreliance on AI 

Generally, overreliance on generative technology can negatively impact humans’ ability to think critically. However, low confidence in AI-generated output is related to increased critical thinking ability, so strategic users may be able to use AI without harming these skills. 

In 2023, around 27% of adults told the Pew Research Center they use AI technology multiple times a day. Some of the individuals in this population may retain their critical thinking skills if they have a healthy distrust of machine learning tools. The data must focus on populations with disproportionately high AI use and be more granular to determine the true impact of machine learning on critical thinking. 

Critical thinking often isn’t taught until high school or college. It can be cultivated during early childhood development, but it typically takes years to grasp. For this reason, deploying generative technology in schools is particularly risky — even though it is common. 

Today, most students use generative models. One study revealed that 90% have used ChatGPT to complete homework. This widespread use isn’t limited to high schools. About 75% of college students say they would continue using generative technology even if their professors disallowed it. Middle schoolers, teenagers and young adults are at an age where developing critical thinking is crucial. Missing this window could cause problems. 

The Implications of Decreased Critical Thinking

Already, 60% of educators use AI in the classroom. If this trend continues, it may become a standard part of education. What happens when students begin to trust these tools more than themselves? As their critical thinking capabilities diminish, they may become increasingly susceptible to misinformation and manipulation. The effectiveness of scams, phishing and social engineering attacks could increase.  

An AI-reliant generation may have to compete with automation technology in the workforce. Soft skills like problem-solving, judgment and communication are important for many careers. Lacking these skills or relying on generative tools to get good grades may make finding a job challenging. 

Innovation and adaptation go hand in hand with decision-making. Knowing how to objectively reason without the use of AI is critical when confronted with high-stakes or unexpected situations. Leaning into assumptions and inaccurate data could adversely affect an individual’s personal or professional life.

Critical thinking is part of processing and analyzing complex — and even conflicting — information. A community made up of critical thinkers can counter extreme or biased viewpoints by carefully considering different perspectives and values. 

AI Users Must Carefully Evaluate Algorithms’ Output