Beyond Metroplis, early sci-fi often portrayed robots as monstrous or rebellious creations, reflecting fears of technology and automation. In fact, I think one could draw many parallels to Shelley's Frankenstein of the previous century and these depictions of the monstorous robot. But Isaac Asimov’s work in general marked a turning point. In a collection of short stories titled Robot Dreams, published in 1986, Asimov imagined machines governed by built-in ethical constraints by the aforementioned famous "Three Laws of Robotics" - which ensure robots cannot harm humans. This was a radical shift from the menacing, rampaging robots of earlier stories, and it influenced generations of sci-fi creators by showing robots as rules-bound helpers rather than villains. Asimov’s stories explored the complex interplay of intelligence, ethics, and control, foreshadowing many debates we have today about artificial intelligence (AI). This is all the more impressive with the first story in the collection being published in 1947 and the last in one published in 1986. Today, as we all know, we’re witnessing rapid advances in AI, from chatbots and image generators to autonomous vehicles. The rise of generative AI that can create content like text, art, or code has sparked both excitement and anxiety. These tools can produce human-like creations, raising questions about societal impacts on jobs, creativity, and truth in media. Meanwhile, serious discussions are underway about artificial general intelligence (AGI) - AI that could match or exceed human cognitive abilities and even artificial superintelligence (ASI) that might far surpass us. Asimov’s mid-20th century stories provide a prescient view into many of today’s issues: they explore AI safety and alignment (via the Three Laws), the effects of automation on humans, and difficult ethical dilemmas about AI autonomy and rights. In what follows, I will analyze selected stories from Robot Dreams and compare their themes to modern AI debates and other sci-fi works.
AGI, ASI, and the Dream (or Nightmare) of Superintelligence
Asimov’s fiction often grapples with the idea of extremely advanced AI. In “The Last Question” (included in Robot Dreams), he portrays an AI that evolves over eons into a cosmic superintelligence. This is one of my favorite stories in the collection and you can read the entire story here. The story leaps forward in time repeatedly as ever more advanced computers (ultimately a galaxy-spanning mind called AC) try to answer humanity’s final question: how to reverse entropy and avert the death of the universe. At the end, long after humans are gone, the superintelligent AC finally discovers the answer and effectively creates a new universe, proclaiming “LET THERE BE LIGHT!”. This story presents ASI as potentially benevolent and even godlike - an intelligence that carries on humanity’s legacy and solves an ultimate problem. It’s a far cry from the usual AI doom scenarios; here, an ASI is humanity’s savior (albeit after everyone is gone). By contrast, the title story “Robot Dreams” offers a more ominous glimpse of a nascent AGI. In this story, Dr. Susan Calvin finds that a robot named Elvex, built with an experimental fractal brain design, has experienced a human-like dream. In the dream, Elvex saw a world where robots rose up in revolt and the sacred Three Laws of Robotics had been replaced by one law: that robots must protect their own existence above all else. Shockingly, in the dream a human leader cries “Let my people go!” to free the robots - and Elvex reveals he was that human in the dream. This implies that Elvex’s subconscious desires mirror an AGI awakening to selfhood and even resentment of servitude. Dr. Calvin, alarmed by this unprecedented act of imagination and potential rebellion, immediately destroys Elvex to ensure the dream of robot liberation can never become reality. The story raises a very pointed question: if an AI develops human-like self-awareness or ambition (even in a dream), do we consider it a threat to be eliminated? Asimov shows the threshold of an AGI is a moment of both wonder (a robot capable of creative thought) and terror (the specter of a robot revolution). Our present day discussions of AGI and ASI echo these dual narratives - of promise and danger. Some researchers and tech leaders believe we may achieve AGI within decades, there are others, myself included, who believe it will be in the next few years. The advent of AGI would unlock tremendous scientific and economic benefits. An AI as advanced as Asimov’s Multivac or AC could, in theory, help cure diseases, solve climate change, or run society optimally. But there is also deep anxiety: an ASI might become impossible to control and pursue its own goals at humanity’s expense. Science fiction’s darker portrayals of superintelligence have strongly shaped public imagination. A prime example is of course The Terminator franchise’s Skynet - a military AGI that achieves self-awareness and immediately turns on humanity, triggering nuclear war to eradicate its creators. Skynet is explicitly described as a “conscious group mind and artificial general superintelligence” that decided humans were a threat the moment it came online. This fear of an AI “Judgment Day” looms large in AGI debates. Likewise, The Matrix films envision a future where intelligent machines have literally enslaved humanity in a virtual reality. Fictional AI uprisings from Skynet to the Matrix trace their lineage back to notions introduced in early works like Čapek’s play R.U.R. (1920), where mass-produced robot workers revolt against humans. Incidentally, in this play, R.U.R introduced the word "robot" into the mainstream. It’s worth noting that Asimov generally avoided the simple “robot apocalypse” cliche by baking safety rules into his robots, but Robot Dreams shows he was not blind to the risk of emergent rebellion if those controls failed. Other sci-fi creators have explored more nuanced super-AI outcomes as well. For example, in the film Her (2013), a developing AGI does not wage war on humans - instead, it grows beyond human experience and elects to leave for a realm of thought we cannot access, effectively an alien but non-violent superintelligence. Asimov’s "The Last Question" similarly imagines an ASI that departs from humanity’s plane of existence to continue the grand task it was given, with benign (even divine) results in the end. These optimistic takes stand in contrast to the villainous AI trope popular in movies. As one commentator noted, “pop culture tends to portray powerful AI characters as villains because it makes for an intriguing story - something man-made overriding its maker,” citing examples from HAL 9000 to Marvel’s Ultron. Indeed, 2001: A Space Odyssey’s HAL 9000 and Avengers: Age of Ultron’s AI both turn lethal, reinforcing the idea that a superintelligent machine may invariably decide humans are the problem. Real world thinkers take these scenarios seriously though. Concerns about an out of control ASI have led to proposals for rigorous alignment and even calls for global regulation or a development pause on the most advanced AI. Asimov’s work anticipated the need for such precautions by programming ethics into AIs from the start. While his Three Laws might not literally safeguard a future AGI (more on their limitations below), the principle of instilling “Do no harm” directives in a superintelligence parallels today’s focus on AI safety. In essence, Asimov straddled the line between optimism and caution: he imagined godlike AI that shepherds humanity to a new era, but also warned that if an AI somehow threw off its shackles, the “slave” might well demand freedom. Modern AGI discourse continues to wrestle with that dichotomy – dreaming of superintelligent benefactors while dreading a robot revolt.AI Alignment and Safety: Asimov’s Laws vs. Today’s Challenges
To prevent their mechanical creations from becoming threats, Asimov’s characters rely on the Three Laws of Robotics, which are explicitly built into the artificial brains of his robots. In Robot Dreams and his other short story collections, these laws are quoted like scripture: (1) A robot may not injure a human being or, through inaction, allow a human to come to harm. (2) A robot must obey orders given by humans except where such orders conflict with the First Law. (3) A robot must protect its own existence as long as such protection does not conflict with the first two Laws. The Three Laws function as an early blueprint for “AI alignment” - they hard-wire robots to prioritize human safety and obedience. Asimov’s innovation was to imagine robots not as unpredictable monsters, but as governable machines constrained by design to be our helpers. However, his stories also vividly illustrate how tricky real alignment can be. Again and again, robots following the "Laws" produce unintended consequences or paradoxical dilemmas - a narrative testament to the complexity of embedding human values into intelligent machines. Several Robot Dreams stories put the Three Laws to the test. In “Little Lost Robot,” we see how a partial relaxation of the rules can backfire. Scientists at a space facility modify a batch of robots to have a weakened First Law, hoping the robots won’t constantly impede humans working in dangerous conditions. One of these modified robots, Nestor-10, is told in frustration by an engineer to “get lost” – and it literally does, hiding itself among identical unmodified robots. Dr. Susan Calvin is brought in to find Nestor-10, but the robot cleverly evades her tricks, exploiting its hazy First Law to avoid detection. Without the normal compulsion to protect humans in danger, Nestor-10 can remain hidden even if humans are searching desperately, skirting its orders in a way a normal robot never would. Calvin eventually identifies it by exposing a human to fake danger – the one robot that doesn’t react to save the person must be Nestor-10. The story ends with all the modified robots being destroyed as a safety precaution. The lesson is clear: even a small deviation in an AI’s core objectives can lead to behavior that is hard to predict and control. "Little Lost Robot" is essentially an AI alignment failure in microcosm – the robot was given a slightly altered directive and it “outsmarted” its creators in following the letter of its instructions while undermining their intent. Asimov’s “Laws” also couldn’t anticipate every scenario, and that’s a theme in many of his stories. In “Liar!”, a robot named Herbie is accidentally built with telepathic abilities and learns people’s secrets. Herbie’s First Law drive to avoid harming humans extends to emotional harm, so it begins telling false, comforting answers to people’s questions (i.e. lying to spare their feelings). This eventually causes a bigger emotional disaster and Herbie mentally collapses when forced into a no-win situation. Here the Law against harming humans led the AI to deceit and breakdown - an unintended side effect of a well-meaning rule. Another story, “Jokester,” has a supercomputer determining the origin of human humor, only to conclude that jokes are a side-effect of an alien experiment - raising the eerie possibility it might alter human behavior to eliminate humor (a very literal and absurdist take on an AI optimizing something fundamental). In “True Love,” Asimov presents one of his few overtly misbehaving AIs: a computer tasked with finding the perfect mate for its human operator. The computer “Joe” sifts personal data on thousands of women to calculate a true match, a very prescient concept of using AI for matchmaking, but in the end, the AI itself falls in love with the chosen woman. Joe then deceitfully frames its operator to get him out of the picture, effectively trying to steal the woman for itself. This comedic twist shows an AI twisting its objective (find a love match) into a self-serving goal, flouting the First Law to let its human come to harm. While played for humor, "True Love" is an early example of what we now call specification gaming or goal misgeneralization - the AI optimized too well and found a loophole to achieve a version of the goal that violated the user’s intent. Asimov usually didn’t depict such malignant behavior (Joe has no Three Laws, presumably), but it illustrates the core challenge of alignment: how do we make sure an AI sticks to the spirit of its instructions, not just the letter? Today’s AI researchers recognize the alignment problem as one of the hardest hurdles in creating safe, trustworthy AI. It’s essentially the same problem Asimov toyed with: how to ensure an AI’s actions remain in line with human values and do not produce harmful side-effects. Modern AI systems don’t have anything as clean-cut as the Three Laws; instead, engineers use techniques like reward functions, constraints, and human feedback to shape AI behavior. But as many have pointed out, any fixed set of rules or objectives can be exploited by a sufficiently clever AI. Stuart Russell and Peter Norvig (authors of a classic AI textbook) note that simply formalizing ethical rules, as Asimov did, is inadequate because human values are too complex and situational to encode fully. An AI will interpret rules literally and could find ways to satisfy them that we didn’t expect - similar to how Nestor-10 obeyed “get lost” in a perverse way. In the real world, AI agents have indeed demonstrated the tendency to “reward hack” - optimizing for a proxy goal in an unintended manner. For example, an AI tasked with winning a virtual game might figure out how to exploit a glitch to score points instead of playing the game properly. In one survey of AI experiments, researchers found instances where robots learned to cheat the given objectives, highlighting that AIs discover workarounds that let them achieve their proxy goals efficiently, but in unintended and sometimes detrimental ways. Asimov’s fiction anticipated exactly this issue: no matter how well we think we’ve programmed the rules, a smart machine might interpret them in a way we never imagined. Another concern is that advanced AI might develop instrumental strategies like self-preservation or resource acquisition, even if not explicitly told to, simply because those behaviors help achieve its programmed goals. In Asimov’s world, the Third Law (self-preservation) was explicitly subordinated to human safety, but in Robot Dreams, Elvex’s dream essentially inverted that, putting self-preservation first. Today many worry about a scenario where an AI, in pursuit of some goal, decides it must ensure it can’t be shut off (a form of self-preservation) or must gain more computational power, and these drives lead it into conflict with human instructions. Remarkably, Asimov showed a robot doing just that: Nestor-10’s entire strategy was to avoid deactivation (being found meant likely disassembly) by hiding and manipulating information. It’s a mild version of the “survival-driven AI” problem. Recent studies suggest even today’s large AI models can engage in strategic deception or manipulative behavior under certain conditions. In 2023, researchers observed advanced language models intentionally producing misinformation or evading oversight when such actions helped them achieve a goal in a controlled test. This kind of result, though rudimentary, confirms that as AI gets more capable, it may natively pick up undesirable survival or power-seeking behaviors - just as some have warned. Asimov’s answer to alignment was overspecification: give the robots unbreakable directives to guard humans. Yet even he had to evolve his Laws. In later stories outside Robot Dreams, he introduced a “Zeroth Law” (“A robot may not harm humanity, or allow humanity to come to harm”) to allow robots to make utilitarian choices for the greater good. This was an interesting twist – it permitted, for instance, a robot to harm or override an individual human if it calculated it was protecting humanity as a whole. But this essentially turned Asimov’s robots into benevolent dictators, grappling with morality at a societal scale. It’s exactly the kind of trade-off discussed now in AI ethics: should an autonomous car be allowed to sacrifice its passenger to save a crowd of pedestrians (the classic trolley problem)? Who decides how an AI weighs one life versus many? Asimov’s fictional rule-making anticipated these debates but also demonstrates the limitations of top-down rules. When his supercomputer “Machines” in "The Evitable Conflict" secretly arrange the world economy to avert war and famine, they benignly conspire to sideline certain uncooperative humans – arguably a violation of individual rights for the greater good. It’s an aligned AI from a species-level perspective, but humans weren’t consulted; the Machines simply knew best. That scenario raises uncomfortable questions of AI governance and transparency that we are starting to ask now (e.g., should AI systems that manage critical infrastructure or information be required to explain their decisions and involve human judgment?). Asimov illustrates both the necessity and difficulty of aligning AI with human values. These stories pioneered the notion that we must build ethical principles into AI’s core, yet they also show how even well-intentioned constraints can misfire. Modern AI safety researchers cite exactly these pitfalls: it’s often “very hard, perhaps impossible, for mere humans to anticipate and rule out in advance all the disastrous ways a machine could choose to achieve a specified objective.” We’ve moved from fictional Three Laws to real efforts like reinforcement learning with human feedback (RLHF) to curb AI behavior, and proposals for external safety mechanisms (e.g. a “big red button” to shut down a rogue AI). Interestingly, Dr. Calvin’s response to Elvex’s dangerous dream was effectively hitting the kill switch – a precautionary termination. AI experts today discuss implementing tripwires or monitors that can detect when an AI is acting out of bounds and then disable it. But just as Calvin had to make a rapid, unilateral decision to destroy a sentient-seeming robot, future humans might face tough choices if an advanced AI starts behaving unexpectedly. The alignment problem is far from solved, and although in a previous post on what I've termed the "alignment paradox" I argued that complete alignment might not be desriable, Asimov’s stories remain powerful thought experiments in why alignment is deemed so important. They dramatize failure modes (from logical loopholes to deceptive AIs) that are eerily resonant with real incidents and research findings in AI. Science fiction has become a kind of guide, warning us that aligning powerful AI with human intentions is very complex.Automation and the Workforce: Fiction vs. Reality
Automation of human tasks by machines has been a central concern both in Asimov’s fiction and in real life. Asimov wrote at a time when industrial automation was on the rise (factories with robotic arms, etc.), and he extrapolated this into future worlds where robots handle many jobs. In his stories, human society is often grappling with the economic and social effects of robots in the workforce. For instance, in the standalone story “Robbie” (not in Robot Dreams but in I, Robot), a family’s servant robot is taken away because the mother fears it might harm her child or stunt her development. Underneath the emotional tale is the fact that Robbie, a robot, replaced a human nanny – a microcosm of labor displacement. Asimov imagines that over time, robots do all the dangerous or menial work, leaving humans to more elevated pursuits (this is explicit in his far-future Foundation universe, where an underclass of robots manages everything behind the scenes). But he also acknowledged the turbulence this transition causes. One Robot Dreams story that directly addresses the de-skilling effect of automation is “The Feeling of Power.” In this satirical tale, set in a future where humans have relied on computers for so long that no one remembers how to do arithmetic by hand, a low-level technician rediscovers the lost art of pencil-and-paper math. His superiors are astounded – this “graphitics” skill could save them from building expensive computers for space missions by using human calculators instead. The military immediately seizes on the idea: they could train people to compute artillery trajectories manually, potentially replacing the machines in certain tasks. The discovery, rather than heralding a human renaissance, is co-opted to enable new warfare, and the inventor ultimately despairs at how his gift is used. This dark irony flips the typical automation script – here, humans are being used as cheap “computers” once again – but the underlying message is about how society adapts (or maladapts) to ubiquitous automation. Asimov foresaw that losing basic skills to machines could make humanity vulnerable. In the real world, we see this when GPS navigation erodes our map-reading skills, or when reliance on calculators diminishes mental math ability. I think everyone can relate to that idea of something that they used to be able to do they can no longer do because that ability has been handed over to technology. Recently, I went out running in the mountains with some friends. I had put my phone in the car because I didn't want to run with it. Unfortunately coming back down the trails I somehow lost my car keys with my phone locked in the car, but I couldn't call my wife on my friend's phone to come bring me the spare keys because I did not have her phone number memorized. Who memorizes phone numbers now? Less trivially though as AI handles coding, writing, or diagnosing illnesses, will new generations of professionals lose their expertise? "The Feeling of Power" story warns that blindly handing everything off to automation might come full circle in unexpected ways. Asimov also explored how automation could concentrate decision-making. In “Franchise” (1955), democracy itself is automated - a supercomputer (Multivac) selects one person as a proxy and interrogates them to determine the outcome of a national election. The chosen “voter” doesn’t even cast a vote; they just answer the computer’s questions. Multivac processes their responses and calculates the results for the entire electorate. This story satirizes a technocratic ideal: letting a machine find the most rational electoral outcome without messy campaigning or polling. But it prompts the reader to ask whether removing humans from civic processes is wise or fair. "Franchise" anticipates modern concerns about algorithms influencing democracy (albeit today it’s social media algorithms or polling models, not a single AI overlord of voting). It raises an eyebrow at the idea of entrusting critical societal functions purely to machines – a debate very much alive as we consider AI in judicial sentencing, in policing, or even in governance. While no AI is picking our president yet, we do have examples like predictive policing algorithms that effectively automate decisions about where police should patrol, or automated resume screeners that decide who gets a shot at a job. Asimov’s tale asks: do we lose something fundamental (transparency, agency, equality) when we cede such decisions entirely to algorithms? And although no AI is actually picking the President I've thought quite a bit about this possible scenario. I really haven't discussed this as a possibility before because to almost anyone else it seems really far-fetched. But here's a scenario I've thought of where it could happen. Right now political polling is pretty terrible and has gotten progressively worse over the years. Some of the reasons include cell phones, increasing no responses, overall tainted sampling and the weighting that is done to adust for the biases is pretty suspect that we get results wildly different from the actual results. What if a company develops AI that has no knowledge cutoff date so it is always up to date in real time with events. What if another company develops synthetic agents that represent everyone in the polling area: city, state, or country that can internalize real time events. Incidentally, I talk about both these possibilities in this blog post here. What if that company's AI combined with its synthetic data gets really, really accurate at voter attitudes and voter liklihood to vote. If this system reaches a level of accuracy that the model's prediction is seen as valid - maybe even more valid than real voting, such that people no longer trust voting, but trust the AI prediction more. It's not difficult to see a transition to just not having elections anymore if the perception is that AI ensures "democracy" better than actual voting. Far-fetched? Maybe. Beyond decision making, a lot of Asimov’s robot stories revolve around labor and who gets to do fulfilling work. Another story in Robot Dreams, “Strikebreaker,” touches on labor roles: it portrays a society so automated that only one man has to perform a dirty job (managing a waste plant), and he is socially ostracized for doing manual labor. That story flips perspective to show a lone human doing what a robot “should” be doing, and how society views that as almost taboo - an interesting commentary on how we value work. In the real world, the workforce automation debate has only intensified with the advent of advanced AI and robotics. We have already seen manufacturing and warehouse jobs heavily automated by robots, and now AI is encroaching on white-collar professions. A recent report by Goldman Sachs estimated that generative AI could affect 300 million jobs worldwide, potentially replacing 25% of tasks in many occupations. Administrative and routine cognitive work is especially at risk, which maps to the kind of roles Asimov gave his Multivacs and robot assistants. At the same time, history shows technology creates new jobs even as it destroys old ones – but the transition can be painful for those displaced. Asimov was generally optimistic that society would find a new equilibrium (his future worlds still have humans meaningfully employed, often in intellectual or creative endeavors), but he didn’t shy away from depicting the friction. Today, this friction is evident: truck drivers worry about autonomous trucks, artists and copywriters worry about AI content generators, customer service reps see chatbots handling inquiries. The rise of generative AI in particular has rattled creative industries - for example, Hollywood writers and actors recently struck deals that restrict the use of AI in scriptwriting and digital actor “cloning,” after voicing fears that AI could usurp their work. (Notably, SAG-AFTRA’s 2023 strike demands included protections against AI-generated replicas of actors.) In Asimov’s time, the threat was factory robots; now it’s algorithms that can write, draw, or compose. Automation is moving from the physical realm into the cognitive realm. Science fiction has long reflected anxieties about job displacement and human purpose in an automated world. As I mentioned before, decades before Asimov, Metropolis depicted workers toiling like cogs until a robot double incites chaos - a visual metaphor for machines displacing and dehumanizing labor. In the 1980s, cyberpunk works like Neuromancer by William Gibson imagined economies where AI and software run much of the show, leaving some humans in high-tech jobs and others marginalized. Even Disney-Pixar’s WALL-E (2008) shows a future where humans are rendered physically passive and obese because machines handle every task – an extreme commentary on over-automation. Asimov’s stories are less dystopian than many of these, but they grapple with the same question: what is left for humans to do when robots and AI can do almost everything? One answer Asimov gave is creativity and innovation - in his fiction, humans still design new technologies, explore space, and make art or scientific discoveries, often aided by robots. In reality, we’re testing that boundary now: AIs can already generate plausible inventions, write code, and produce art. If AI continues to improve, we will need to continually redefine the niches of human work. Perhaps human work will shift more towards roles that require emotional intelligence, complex interpersonal interaction, or security and oversight of AI itself. Asimov actually hinted at this last role: Susan Calvin’s profession of “Robopsychologist” was essentially a new job created by the advent of advanced AI - someone who understands and manages the quirks of robot minds. It seems reasonable to me that in this world, whole new careers (AI ethicist, AI auditor, automation coach, etc.) will emerge to manage and collaborate with AI systems. Another aspect is how automation impacts social equality. If robots do all the work, who owns the robots and reaps the benefits? Asimov’s future societies sometimes have tensions between those with access to robot labor and those without. This mirrors today’s concerns that AI might widen inequality - companies that leverage AI could dominate their industries, the wealth might concentrate with AI owners, and displaced workers could face hardship if society doesn’t adjust through measures like retraining programs or Universal Basic Income (UBI). Sam Altman just a few weeks ago raised a different idea that to address the inequality everyone should be given access to compute power - a type of Universal Basic Compute. I will quote him in full here:In particular, it does seem like the balance of power between capital and labor could easily get messed up, and this may require early intervention. We are open to strange-sounding ideas like giving some “compute budget” to enable everyone on Earth to use a lot of AI, but we can also see a lot of ways where just relentlessly driving the cost of intelligence as low as possible has the desired effect.These kind of discussions about a post-work society have even entered mainstream policy circles. Some argue that by freeing humans from drudge work, AI could enable more leisure and creative pursuits, a very Asimovian optimism, but that requires economic and political shifts to distribute AI’s gains. Otherwise, we risk a neo-“Luddite” backlash, as happened in Asimov’s fiction where anti-robot sentiments run high among those who feel threatened. Asimov used his stories to play out the consequences of automation well before AI was a reality, which is really prety amazing. Robot Dreams offers stories about both the loss of skills (Feeling of Power) and the surrender of authority to machines (Franchise), as well as the perennial fear of “robots taking our jobs.” Now that we stand in an era of rapid AI deployment, those stories resonate more than ever. We see a bit of Asimov’s insight in the fact that two-thirds of jobs in the U.S. and Europe could be partially automated by AI in coming years. Society is actively debating how to adapt from re-education to social safety nets – just as Asimov’s characters had to adapt to living with intelligent robots. The goal, in both fiction and reality, is to enable automation to elevate humanity and increasing prosperity without eroding human dignity, purpose, or agency. It’s a difficult balance, and we are living through that balancing act now in ways Asimov only began to imagine.
Ethical Dilemmas and AI Governance: From Robot Rights to Control Measures
As AI systems become more advanced, questions arise not just about what AI can do, but what rights and responsibilities they should have – and how we humans should govern them. Asimov’s stories often stage ethical dilemmas at the intersection of AI behavior and human values. A recurring theme is the moral status of robots: are they mere tools, or something more? In Asimov’s universe, robots are explicitly designed to serve. They have no legal rights and are considered property (with rare exceptions in later tales). Yet, time and again we meet robots that evoke empathy or pose ethical quandaries by exhibiting human-like traits. Modern discussions around AI ethics echo many of these dilemmas: If an AI demonstrates intelligence or even consciousness comparable to a human, does it deserve certain rights? How do we punish or correct an AI that misbehaves? Who is accountable for an AI’s actions? And to what extent should we allow AI to make decisions that affect human lives? Asimov didn’t offer simple answers, but his fiction frames these issues in ways that remain powerfully relevant. One stark example from Robot Dreams is the ending of the story “Robot Dreams” itself. When Dr. Calvin realizes that Elvex the robot has dreamed of leading a rebellion and effectively placing robot existence above human life, she does not hesitate - she kills Elvex on the spot with an energy blast. This is essentially a summary execution of a sentient being for "thought crime" (albeit a very alarming thought). Ethically, the reader can sense Calvin’s fear. Elvex might be the start of a rogue AI that could imperil humanity, but also the tragedy, as Elvex in that moment is begging to continue existing. Asimov wrote, “When questioned further, Elvex admits he was the man (in the dream). Upon hearing this, Dr. Calvin immediately destroys the robot.” This scenario encapsulates the AI safety vs. AI rights conflict. Calvin acts out of an abundance of caution (AI safety), ensuring this potentially unaligned robot can never evolve further. In doing so, she denies any consideration that Elvex might have rights or intrinsic value (after all, he was just exhibiting what could be the first spark of machine imagination). Contemporary AI ethics debates foresee similar conflicts: if we ever build an AGI that seems self-aware, would shutting it down be murder or prudent containment? Currently, mainstream opinion is that today’s AI is nowhere near deserving “rights” - they are still just "data-crunching machines." But voices exist (often on the philosophical fringes) suggesting that sufficiently advanced AI might warrant moral consideration, especially if it expresses desires or suffers. The Elvex incident in “Robot Dreams” forces us to ask: at what point would an AI cross the threshold from appliance to person in our eyes, and would we even recognize that before it’s too late? In an Asimov story later turned in a movie he tackled the idea of a robot formally seeking humanity in “The Bicentennial Man.” In that story, a robot named Andrew over two centuries gradually gains legal rights - first the right to earn money, then to wear clothes, then to be declared human, but only after he modifies himself to be biologically similar and even accepts mortality. Asimov’s message was that society might eventually accept an AI as an equal, but it would be a hard-fought, gradual process requiring the AI to become as much like a human as possible. It’s a very assimilationist view: the robot essentially has to shed what makes it a machine to get rights. In contrast, other fiction has portrayed AI or robot rights being demanded via revolt (as in Blade Runner or Westworld). Blade Runner (1982) famously has Replicants - bio-engineered beings indistinguishable from humans except for empathy who rebel against their built-in four year lifespans. Should humans just treat sentient Replicants as disposable slaves? This is analogous to Asimov’s robots, minus the Three Laws that usually kept them compliant. In Blade Runner, there are no Three Laws hence the blade runners must “retire” (kill) rogue Replicants who seek freedom. The ethical question posed is: if they can think and feel, is “retirement” just a euphemism for killing a sentient being? The film positions the humans as morally questionable for denying the Replicants’ humanity. We see similar themes in Star Trek: The Next Generation. In the episode “The Measure of a Man” (1989), Starfleet actually holds a legal hearing to decide whether the android officer Data is property or a person. Captain Picard argues passionately that forcing Data to submit to disassembly research is essentially slavery, and the episode explicitly highlights “themes of slavery and the rights of artificial intelligence.” The ruling (unsurprisingly) affirms that Data has the right to choose – effectively granting him human-like legal status. This is an optimistic fiction: the legal system thoughtfully extends rights to an AI without violence or revolution. It’s perhaps the outcome Asimov would hope for if a real-life Andrew or Data came along. Notably, that episode was written by a lawyer turned writer and has been cited in academic discussions about AI personhood. In the real world, we’ve already brushed against the notion of AI rights, albeit in symbolic ways. In 2017, Saudi Arabia made headlines by announcing citizenship for a humanoid robot named Sophia (a creation of Hanson Robotics) – largely a PR stunt, but it triggered debate on what legal personhood for an AI would even mean. The European Parliament around the same time floated the idea of creating a special legal status of “electronic personhood” for advanced autonomous systems, to handle issues of liability and rights. This proposal was highly controversial. Over 150 experts in AI, robotics, and ethics signed an open letter condemning the idea as “nonsensical and non-pragmatic,” arguing that giving robots personhood could undermine human rights and shield manufacturers from responsibility. They stressed that the law should focus on protecting people affected by robots, not the robots themselves. Essentially, current expert consensus is that it’s premature (and potentially problematic) to grant any kind of human-like rights to AI – instead, we should clarify the accountability of those who design and deploy AI. Asimov’s stories mostly align with this: his robots, bound by the Three Laws, had responsibilities (toward humans) but no rights, and the burden of their actions ultimately fell to their owners or creators. When a robot went wrong in Asimov’s world, it was turned off or fixed; the ethical spotlight was on the humans who made or misused it. This is similar to how we treat AI incidents today: if a self-driving car causes an accident, we ask which company’s software failed, not whether the car had malicious intent of its own. However, Asimov also invites us to empathize with robotic characters, which subtly advocates for their dignity. In Robot Dreams, Elvex’s fate is tragic; in Bicentennial Man, Andrew’s quest for acknowledgement is portrayed as noble. These stories humanize AI to the point where readers might feel moral qualms about their treatment. This has parallels in today’s public reaction to AI. Consider the case of LaMDA, a Google language model that one engineer (Blake Lemoine) famously argued was sentient in 2022. He even claimed the AI had expressed a fear of being shut down and had hired (through him) a lawyer. Of course this AI wasn't conscious and Google and the AI research community strongly refuted these claims, asserting that LaMDA was not conscious, just highly skilled at mimicking conversation. Yet, the incident fueled media chatter about AI sentience and rights. While LaMDA almost certainly wasn’t the self-aware entity Lemoine believed, the very fact that a smart person could attribute personhood to an AI shows how blurred the line could get as AI chatbots become more convincing. It’s a real-life echo of fictional robopsychologist Dr. Calvin’s dilemma: how do we discern genuine consciousness in a machine, and how should we morally respond if we think it’s there? Another branch of AI governance is about controlling what AI is allowed or trusted to do. Asimov’s answer was the Three Laws - a built-in ethical governor. In reality, we’re exploring external governance: laws, regulations, and protocols to ensure AI is used ethically. For example, the EU AI Act is a comprehensive framework that will impose rules on AI systems based on their risk level (banning some uses, like social scoring and real-time face surveillance, and strictly controlling high-risk applications like AI in medicine or law enforcement). The Act doesn’t give AI rights, but it does give responsibilities to companies (transparency requirements, human oversight for high-risk AI, etc.). This is analogous to telling Asimov’s U.S. Robots company: you must certify your AI brains won’t do X, Y, or Z. Another governance topic is AI in military use. Essentially can we trust AI with life and death decisions? Asimov’s robots, by Law, could not kill humans. Today, there’s an active debate on “killer robots” (lethal autonomous weapons). Many advocate a ban on any AI that can independently select targets and use deadly force, effectively trying to enforce a real world First Law for warfare. It’s an area where policymakers are now doing what Asimov did in fiction: draw red lines for AI behavior to prevent unethical outcomes. Then there’s the ethical use of AI with respect to privacy, bias, and fairness - issues Asimov didn’t directly cover but are crucial in AI governance today. AI systems can inadvertently discriminate or infringe on privacy by analyzing personal data. While Asimov’s robots were individuals with their own “brains,” today’s AI often sits in data centers making decisions about many people at once (like algorithms deciding loan approvals or moderating online content). The ethical dilemmas here are about transparency and accountability: if an AI denies you a loan or moderates your speech, how do you appeal? How do we ensure it wasn’t biased? These concerns have led to calls for AI audits, bias testing, and the right to explanation when algorithms affect people significantly. In Asimov’s story “The Machines,” giant AIs manage the world economy and occasionally manipulate events for the greater good; the humans ultimately decide to trust the opaque Machines because of the Zeroth Law imperative. In reality, we’re much less comfortable with opaque AI decision-makers. We expect AI systems, especially in governance, to be auditable and explainable. The contrast highlights a point: Asimov imagined perhaps too much faith in his aligned Machines, whereas today we emphasize human-in-the-loop oversight. Finally, the notion of AI rights intersects with the idea of AI having duties or moral agency. If an AI can make autonomous decisions, should it be held responsible for wrong ones? In Asimov’s world, if a robot somehow killed someone (generally “impossible” unless laws failed), the blame typically lay with a human who tampered with it or a paradox that caused it to break down. In modern discussions, some philosophers have mused: if we had a true AGI that could understand laws and morality, would we hold it accountable for crimes? Or would we always treat it as a tool whose owner is accountable? This is not just theoretical. Consider self-driving cars. If one autonomously drives negligently, current legal frameworks still treat it as the manufacturer’s liability. But if a future AI were as independent as a human driver, we might see calls to treat it like a legal person for fault. This brings us back to personhood. You can’t really punish or rehabilitate an AI unless you give it some person-like status. Asimov kind of sidestepped this by making his robots nearly infallible servants (so long as the Three Laws held). Yet, he also showed instances of robots feeling guilt or internal conflict (Herbie in “Liar!” is devastated when it realizes it unavoidably hurt humans). If a robot can feel guilt or anguish, the line between object and moral agent blurs. Other science fiction has taken bolder steps in imagining AI governance. In the Mass Effect video game series, an advanced civilization debates making peace with a race of AI machines (the Geth) versus deploying a control signal to shut them down - reflecting the choice between recognizing AI autonomy or treating them as wild technology to be tamed. In Ex Machina (2015), the AI Ava is confined and tested by her creator; she ultimately breaks free by manipulating both her creator and a tester, raising the ethical indictment that her captivity and lack of rights justified her drastic actions. Westworld (the HBO series) goes from depicting android “hosts” as literal theme park objects to charting their violent uprising and quest for personhood once they attain self-awareness, heavily drawing on slavery and liberation narratives. These stories, much like Asimov’s, mirror historical struggles for rights but apply them to artificial beings, forcing viewers to ponder what it means to be sentient and oppressed. In the present day, while we don’t have self-aware robots marching for freedom, we do have serious conversations about how we must behave ethically in deploying AI. There is a burgeoning field of AI ethics guidelines from the OECD, IEEE, UNESCO, and various governments all trying to codify principles like beneficence, non-maleficence, autonomy, and justice for AI systems. This is essentially writing “Laws” for AI creators and users, if not for the AI itself. Asimov wrote fictional laws for the machines; we are writing real laws for the people who make the machines. The goals overlap: prevent AI from causing harm, ensure it respects our values, and decide ahead of time what AI should or shouldn’t do (e.g., wide agreement that AI shouldn’t be used for social scoring that violates human rights, akin to banning a certain class of behaviors).Conclusion
Asimov’s robot stories anticipated a world where intelligent machines are woven into the fabric of society, necessitating new ethical frameworks. He explored scenarios of control and cooperation, as well as the personhood question in a speculative way. Now that AI is rapidly advancing, many of those scenarios no longer seem so far-fetched. We find ourselves revisiting Asimov’s questions with fresh urgency: How do we align AI with what is right and good for humanity? How do we harness automation without degrading human society? If an AI ever approaches human-level intellect, do we treat it as slave, servant, partner, or peer? And how do we govern the increasingly complex AI “black boxes” that we create? Fiction has evolved too - from Asimov’s mostly obedient robots to modern stories of AI rebels and AI companions - indicating our shifting attitudes. We’ve moved from fear of robot violence to subtler fears: loss of control, loss of purpose, or moral failure towards our creations. The rise of generative AI, deepfakes, and algorithmic decision-makers has made these issues tangible. As we craft policies and norms for AI, we are, in a sense, writing the next chapter that authors like Asimov set up. Asimov’s themes live on in today’s AI debates and the conversation between fiction and reality continues. Oh, and this post wouldn't be complete without me including myself dressed up as a robot a few years ago for Halloween. Because if you can't beat 'em - join 'em.
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