The Flawed Heuristic of Language and Intelligence
People often use mental shortcuts, or heuristics, to assess intelligence through language fluency. The assumption that speech ability equates to intelligence has historically harmed disabled individuals, particularly those with speech difficulties. With modern AI advancements, this heuristic is failing in a new, widespread manner, leading many to overestimate artificial intelligence while continuing to misjudge nonspeaking humans.
Nonspeaking Individuals Are Misunderstood
Historically, individuals with speech impairments, such as nonverbal autistic people or those with verbal apraxia, have been inaccurately assumed to have low intelligence. Many nonspeaking children fully understand language but remain trapped without alternative communication tools. Their intellectual abilities often emerge only when given access to assistive technologies like Augmentative/Alternative Communication (AAC) or letterboards. However, due to the persistent misconception that speech reflects intelligence, these tools remain underutilized, leaving countless individuals unheard.
AI-Language Models Lack True Understanding
Conversely, the emergence of AI-powered large language models (LLMs)—such as ChatGPT—has revealed the opposite side of this flawed heuristic. Because LLMs generate fluid, human-like text, people mistakenly attribute intelligence, comprehension, and even sentience to these tools. However, these AI systems do not understand language the way humans do; they are merely sophisticated pattern-matching programs that rely on statistical probabilities to form coherent sentences without grasping their meaning.
Misleading AI Design Choices
Tech companies intentionally shape AI interactions to mimic human behavior, reinforcing the illusion of intelligence. Features like apologetic responses, friendly tones, and memory-like session continuity encourage users to perceive AI as self-aware. However, these are only design choices meant to create a more engaging—and profitable—user experience. Despite appearances, AI programs do not learn from conversations in real time, nor do they possess reasoning, intent, or an internal model of the world.
The Financial Motives Behind AI Hype
Despite AI’s well-documented limitations, many prominent voices—including tech executives and researchers—continue to exaggerate its capabilities, often for financial gain. Companies invest in promoting AI as highly intelligent, potentially even sentient, which fuels public fascination and drives revenue. This exaggeration also shifts attention away from the real harms caused by current AI implementations, such as misinformation, job displacement, surveillance risks, and bias in automated decision-making.
An Urgent Need to Rethink AI and Intelligence
The dual misconceptions—overestimating AI’s intelligence while underestimating disabled individuals—highlight the need to rethink how we assess human and artificial intelligence. Over the next few years, as AI failures become more apparent, people will likely recognize the limitations of language-based heuristics when evaluating machines. However, this shift should also extend to human cognition; we must challenge old biases and ensure that alternative communication methods are widely recognized and utilized for those who need them.
Conclusion: Separating Language Ability from Intelligence
Society must move beyond the flawed assumption that language fluency and intelligence are interchangeable. While AI and large language models may simulate competent conversation, they lack true comprehension. Meanwhile, many nonspeaking individuals possess intellectual capabilities that are ignored due to outdated perceptions. By fostering awareness of these issues, we can develop more ethical AI applications and support inclusive communication for all people, regardless of their speaking ability.
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