Artificial Intelligence: A Guide for Thinking Humans (2019): Can Machines Equal Human Intelligence Ever

Written by Melanie Mitchell, Artificial Intelligence: A Guide for Thinking Humans, offers a profound knowledge of artificial intelligence (AI) from both a technical and philosophical perspective. Mitchell is a professor of computer science at Portland State University.

Rather than merely celebrating AI’s achievements, Mitchell critically examines its contemporary capabilities, future prospects, and the ethical and societal implications.

The personal and insightful nature of this book sets it apart from purely technical guides, making it accessible to general readers while still engaging for those familiar with AI.

It is one of the 10 books that I have been reviewing, e.g, The Age of AI: And Our Human Future, Superintelligence: Paths, Dangers, Strategies, Human Compatible, 2084: Artificial Intelligence The Future of Humanity, Our Final Invention, The Singularity Is Nearer, Four Battlegrounds, The Alignment Problem, Artificial Intelligence: A Guide For Thinking Humans and Life 3.0.

Key Takeaways from

1. The Illusion of Rapid Progress

One of Mitchell’s central arguments is that AI progress, while remarkable in some areas, is often overhyped.

She emphasizes that AI systems like those created by Google and DeepMind have achieved remarkable feats—beating humans at games like Chess and AlphaGo or AlphaZero, but their success is primarily limited to highly domain-specific specialized tasks.

Mitchell challenges the assumption that these advances bring us closer to general AI, which would require machines to think, reason, and adapt like humans.

Her discussion of Douglas Hofstadter’s skepticism about AI’s ability to truly emulate human thought highlights the depth of the challenge AI researchers face. He was disturbed that Kurzweil’s books “mixed in the zaniest science fiction scenarios with things that were very clearly true.”

The “Bag of Tricks” Problem

Mitchell touches on the unsettling idea that AI, despite its sophistication, might not actually be “intelligent” in a human sense.

She explores whether human abilities, such as creativity, empathy, and emotions, are merely reducible to algorithms. This “bag of tricks” theory suggests that AI might not truly understand the world but instead simulates understanding through brute-force computation.

Mitchell argues that even the most impressive AI systems, like GPT or autonomous vehicles, lack genuine common sense and flexible reasoning, traits that come naturally to humans.

Ethical Implications and the Singularity

Mitchell delves into the ethical questions surrounding AI, especially the potential risks of developing AI systems that could surpass human intelligence—a concept known as the Singularity.

While some AI researchers, like Ray Kurzweil, predict this event within the next few decades, Mitchell takes a more cautious stance.

She argues that we need a clearer understanding of both human intelligence and AI before making such predictions. Moreover, she warns against blindly rushing towards this future without considering the social, economic, and moral consequences.

Common Sense is the Real Challenge

The author highlights how tasks that are simple for humans, such as understanding language in context, recognizing everyday objects, or using basic common sense, remain extraordinarily difficult for AI.

This paradox—wherein tasks considered easy for humans are hard for AI—reflects the complexity of replicating the nuanced ways in which human intelligence operates.

Mitchell uses examples like facial recognition and language translation to show how AI, though advanced in some respects, struggles with ambiguity, context, and deeper understanding.

The Importance of Human Intelligence in the AI Debate

Throughout the book, Mitchell emphasizes the unique nature of human intelligence.

While machines excel at computation and pattern recognition, human intelligence involves an intricate blend of perception, emotion, and contextual understanding. The book challenges readers to reconsider what we mean by “intelligence” and to appreciate the extraordinary complexity of the human mind.

AI’s strength in narrow domains, contrasted with its weaknesses in general understanding, leads to a re-evaluation of the true nature of intelligence itself.

Human vs. AI Creativity

Speaking of AI creativity taking place over humans, Mitchell mentions EMI (Experiments in Musical Intelligence), an AI-based music composer invented by musician David Cope. She cites Hofstadter saying, “I was terrified by EMI. Terrified. I hated it, and was extremely threatened by it. It was threatening to destroy what I most cherished about humanity. I think EMI was the most quintessential example of the fears that I have about artificial intelligence.”

EMI helped David Cope create music in the style of classical composers such as Bach and Chopin.

Hofstadter was shocked to find EMI creating pieces that were equal to the great musicians. To him, “it feels like there is nothing more human in the world than that expression of music”.

Literary scholar Jonathan Gottschall has observed, “Art is arguably what most distinguishes humans from the rest of creation”.

Like music, we will lose other areas of creativity to AI, like ChatGPT. A report on the Washington Post, published on November 14, 2024, reveals that people prefer ChatGPT poems over William Shakespeare, Emily Dickinson, T.S. Eliot or Sylvia Plath. “I was terrified by the scenarios. Very skeptical, but at the same time, I thought, maybe their timescale is off, but maybe they’re right. We’ll be completely caught off guard. We’ll think nothing is happening and all of a sudden, before we know it, computers will be smarter than us”.

Mitchell adds that “he was terrified that intelligence, creativity, emotions, and maybe even consciousness itself would be too easy to produce—that what he valued most in humanity would end up being nothing more than a “bag of tricks,” that a superficial set of brute-force algorithms could explain the human spirit”.

However, intelligence is not always IQ, it encompasses different dimensions such as emotional, verbal, spatial, logical, artistic, social, and so forth.

Then she pronounces the terrifying statements about the capabilities of AI that humans are hoping to achieve for their easiness. “If such minds of infinite subtlety and complexity and emotional depth could be trivialized by a small chip, it would destroy my sense of what humanity is about.”

That AI is taking over all of the creative human enterprises gradually and giving us unprecedented opulence in turn are in fact extremely costly phenomenon.  The author notes, “AI will solve all our problems, put us all out of a job, destroy the human race, or cheapen our humanity. It’s either a noble quest or “summoning the demon.”

“Deep Blue may have beat Kasparov, but it didn’t get any joy out of it.”) Although, Max Tegmark provides a philosophical, psychological and scientific blueprint of “consciousness” and how it works, Mitchell says that “AI researchers haven’t yet figured out how to encode “intuition” into an evaluation function”.

For humans, a crucial part of intelligence is, rather than being able to learn any particular skill, being able to learn to think and to then apply our thinking flexibly to whatever situations or challenges we encounter.

Struggling for decades to understand and reproduce—commonsense knowledge, abstraction, and analogy, among others—but these abilities have proven to be profoundly elusive. Other major questions remain: Will general AI require consciousness? Having a sense of self? Feeling emotions? Possessing a survival instinct and fear of death? Having a body? As I quoted Marvin Minsky earlier, “This is still a formative period for our ideas about mind.”

AI and Language

One of the fascinating facts Mitchell poignantly mentions is the current unsatisfactory capability of AI in terms of commonsense and language comprehension.

True, that the current AI translation skill is inadequate, I regularly encounter that inadequacy when I do bilingual translation work. Mitchell duly states that, “Translation is far more complex than mere dictionary look-up and word rearranging.… Translation involves having a mental model of the world being discussed.”

Mitchell goes on, “Most recently, this statistical data-driven approach has focused on deep learning. Can deep learning, along with big data, produce machines that can flexibly and reliably deal with human language?

This is exactly what I would concur with Mitchell “, For now, I’ll simply say that while neural machine translation can be impressively effective and useful in many applications, the translations, without post-editing by knowledgeable humans, are still fundamentally unreliable”. While deep learning has produced some very noteworthy progresses in speech recognition, language translation, sentiment analysis, and other areas of NLP (natural language processing), human-level language processing remains a distant goal.

“When AI can’t determine what ‘it’ refers to in a sentence, it’s hard to believe that it will take over the world.”

For language to understand we must understand context first, and we need commonsense in doing so. Therefore, Mitchell rightly puts, “While natural-language processing by machines has come a long way, I don’t believe that machines will be able to fully understand human language until they have humanlike common sense”.

But essentially everyone in AI research agrees that core “commonsense” knowledge and the capacity for sophisticated abstraction and analogy are among the missing links required for future progress in AI.

Personal Reflection

Mitchell’s book resonates deeply with my concerns about AI’s societal impacts. As someone who follows AI developments closely, I found her cautionary approach refreshing.

While the AI field is filled with optimism and grand predictions, Mitchell brings a necessary balance by highlighting the significant gaps between current AI systems and human-like intelligence.

Her emphasis on the dangers of overestimating AI’s capabilities, especially in the realms of ethics and social disruption, is a critical reminder that we must approach this technology with both excitement and caution.

Conclusion

In conclusion, Artificial Intelligence: A Guide for Thinking Humans offers a thought-provoking and balanced view of AI.

Mitchell invites readers to question the hype surrounding AI while acknowledging its potential.

Her nuanced approach encourages deeper reflection on the role AI will play in shaping our future, urging us to remain thoughtful and critical as we navigate this technological revolution.