NPR84%

'Self-aware' robots can learn complex tasks by watching humans. Is that a good thing? 

By Katia Riddle0%

4/24/2026, 10:00:00 AM

BS Summary: The article has not yet been analyzed.

'Self-aware' robots can learn complex tasks by watching humans. 
Is that a good thing? 
Scientists say they've made a key breakthrough that would allow robots to figure out complex tasks on their own, but experts say it raises questions about how much risk comes with letting robots be in charge of their own learning. 
Imagine a robot that could do your laundry, make your bed, cook your dinner, or stock the dairy section at your local grocery store. 
Humans have long been able to teach robots how to do individual tasks, but instructing them on these more sophisticated jobs has been an elusive goal, despite billions of dollars invested into robotics. 
Now, a team of scientists in Switzerland has made progress in the quest to invent helpful robots that can act on complex instruction from humans. 
The development raises questions about whether this kind of technology could someday learn not only to help humans, but to also become capable of harming them. 
Inventing the personal barista 
For years, robotics scientist Sthithpragya Gupta has been dreaming about the things his robot might do. 
"I personally want the robot to make me a coffee," says Gupta. 
He and his colleagues at École Polytechnique Fédérale de Lausanne  an engineering school in Switzerland  keep late hours at their lab in the Swiss Alps. 
"There's a lot of coffee consumption," says Gupta. 
"If I could just say 'a little bit of sugar, a bit more creamer,' stuff like that," he says. 
"That would be a dream come true." 
A problem that robotics scientists and engineers like Gupta have long battled is that robots cannot do tasks beyond those they are specifically programmed for. 
Gupta uses a tennis example to explain the issue. 
Robots may be able to learn how to hit a backhand shot, he explains. 
They can backhand that ball perfectly again, and again, and again. 
But if conditions change  say, their opponent moves, or the light changes  it all falls apart. 
Humans have no problem adjusting to these kinds of changes. 
Teaching a robot how to adapt, though, is much more difficult. 
"It's very difficult to transfer this behavior from humans to robots," says Gupta. 
Until now, he hopes. 
Gupta and his colleagues have published a paper in the journal Science Robotics demonstrating a new way of teaching robots using machine learning, a type of artificial intelligence. 
The approach relies on kinematic intelligence  a robot's built-in awareness of how its own body can move safely through space. 
In a video demonstrating their technology, robots with a single arm attached to a base watch as a human instructor tosses a ball into a small container. 
The robots then pick up the ball and copy the instructor's behavior, adjusting for their own position and accommodating their non-human bodies. 
Robots are then capable of transferring these skills and knowledge to other robots. 
"It could be a turning point," says Robert Platt, who studies engineering and robotics at Northeastern University. 
Platt, who called the work a "breakthrough," noted that the field of robotics is not in widespread agreement about the path forward to creating effective robots through machine learning  but that most agree the problem these researchers are tackling is a critical one. 
"More people may do this in the future," he said. 
Platt was hesitant to forecast any particular timeline for robots becoming widespread household accessories. 
"We're at a point of very fast change," he notes. 
" Part of the reason why I hesitate to make predictions  look what happened with large language models," he says, referring to generative AI chatbots such as ChatGPT or Claude that have been widely adopted. 
"We were a long way away and then all of a sudden  we weren't." 
A fine line between self-awareness and consciousness 
If a robot can self-correct and teach others, does that make it self-aware? 
" It looks like this robot is capable of doing some very impressive feats of learning," says Susan Schneider, who studies artificial intelligence at Florida Atlantic University. 
"But that doesn't mean something has full-blown consciousness or inner awareness in the sense that biological beings have it." 
Schneider points out that a critical distinction between robots and humans is feeling. 
"Consciousness is the felt quality of experience," she says. 
"When you sip your morning espresso shot, when you see the richness of the sunset, when you have a headache, it feels like something from the inside to be you." 
But this lack of consciousness poses new questions about ethics. 
"It immediately raises alarm bells in any AI safety researcher's mind," says Schneider. 
Later versions of this kind of technology, she says, could potentially be weaponized against humans. 
Researchers have taken care to include safety protocols to ensure that robots aren't able to hurt people. 
Even they acknowledge, however, that future development of this technology will need guardrails. 
" I think really soon we should have regulatory frameworks on who operates a robot and how," says Gupta. 
Humans are at an inflection point with robotics, says Susan Schneider. 
"It's a very exciting time," she says, "and we just don't know where it's headed." 
Article reasoning-pattern comparisonThis article: 0.0%Katia Riddle: 2.2%Goats and Soda (NPR): 3.4%Confirmation Bias0.0%This article: 0.0%Katia Riddle: 0.3%Goats and Soda (NPR): 1.6%Anchoring Bias0.0%This article: 1.7%Katia Riddle: 2.0%Goats and Soda (NPR): 3.8%Availability Heuristic1.7%This article: 0.0%Katia Riddle: 0.9%Goats and Soda (NPR): 1.2%Representativeness Heuristic0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.8%Hindsight Bias0.0%This article: 0.0%Katia Riddle: 0.8%Goats and Soda (NPR): 2.4%Overconfidence Bias0.0%This article: 1.1%Katia Riddle: 0.9%Goats and Soda (NPR): 11.1%Framing Effect1.1%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 1.2%Loss Aversion0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 1.1%Status Quo Bias0.0%This article: 3.8%Katia Riddle: 0.3%Goats and Soda (NPR): 0.2%Sunk Cost Effect3.8%This article: 8.7%Katia Riddle: 13.5%Goats and Soda (NPR): 3.4%Optimism Bias8.7%This article: 4.7%Katia Riddle: 0.8%Goats and Soda (NPR): 2.3%Pessimism Bias4.7%This article: 7.2%Katia Riddle: 2.8%Goats and Soda (NPR): 11.3%Negativity Bias7.2%This article: 0.0%Katia Riddle: 1.5%Goats and Soda (NPR): 2.3%Self-Serving Bias0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 1.1%Fundamental Attribution Error0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.3%Actor-Observer Bias0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 2.3%In-Group Bias0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 1.2%Out-Group Homogeneity Bias0.0%This article: 0.0%Katia Riddle: 3.2%Goats and Soda (NPR): 2.8%Halo Effect0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.3%Horn Effect0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Katia Riddle: 0.4%Goats and Soda (NPR): 1.7%Recency Bias0.0%This article: 0.0%Katia Riddle: 0.2%Goats and Soda (NPR): 0.5%Primacy Effect0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.1%Blind-Spot Bias0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 1.2%Ad Hominem0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.3%Straw Man0.0%This article: 5.0%Katia Riddle: 8.0%Goats and Soda (NPR): 6.1%Appeal to Authority5.0%This article: 0.0%Katia Riddle: 1.9%Goats and Soda (NPR): 1.5%False Dilemma0.0%This article: 4.7%Katia Riddle: 1.8%Goats and Soda (NPR): 1.3%Slippery Slope4.7%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.1%Circular Reasoning0.0%This article: 4.1%Katia Riddle: 2.6%Goats and Soda (NPR): 4.4%Hasty Generalization4.1%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.3%Red Herring0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.7%Bandwagon0.0%This article: 1.5%Katia Riddle: 1.9%Goats and Soda (NPR): 6.6%Appeal to Emotion1.5%This article: 0.0%Katia Riddle: 0.3%Goats and Soda (NPR): 0.9%Begging the Question0.0%This article: 0.0%Katia Riddle: 0.5%Goats and Soda (NPR): 2.8%Post Hoc (False Cause)0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.2%Tu Quoque0.0%This article: 0.0%Katia Riddle: 0.8%Goats and Soda (NPR): 0.4%Burden of Proof0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.2%Appeal to Nature0.0%This article: 0.0%Katia Riddle: 0.5%Goats and Soda (NPR): 0.2%Composition/Division0.0%This article: 0.0%Katia Riddle: 8.6%Goats and Soda (NPR): 2.8%Anecdotal0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.1%No True Scotsman0.0%This article: 1.5%Katia Riddle: 1.9%Goats and Soda (NPR): 1.5%Ambiguity (Equivocation)1.5%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.0%Gambler’s Fallacy0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.1%Middle Ground0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.1%Personal Incredulity0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.2%Special Pleading0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.5%Genetic Fallacy0.0%This article: 0.0%Katia Riddle: 1.8%Goats and Soda (NPR): 1.3%Unattributed Quote0.0%This article: 0.0%Katia Riddle: 0.6%Goats and Soda (NPR): 0.9%Quote-first Misdirection0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 3.1%Biased Writer Voice0.0%This article: 2.2%Katia Riddle: 0.0%Goats and Soda (NPR): 1.0%Indoctrination2.2%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Katia Riddle: 0.0%Goats and Soda (NPR): 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Katia Riddle: 3.8%Goats and Soda (NPR): 0.3%Attempt to Sell a Product or S…0.0%

872 words analyzed.

Speakers

3speakers39%attributed speech529writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 40 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageSthithpragya Gupta • 12 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageSthithpragya Gupta • 8 words • 0.0% coverageSthithpragya Gupta • 19 words • 0.0% coverageSthithpragya Gupta • 7 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageSthithpragya Gupta • 14 words • 0.0% coverageSthithpragya Gupta • 11 words • 0.0% coverageSthithpragya Gupta • 18 words • 0.0% coverageSthithpragya Gupta • 10 words • 0.0% coverageSthithpragya Gupta • 11 words • 0.0% coverageSthithpragya Gupta • 13 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageRobert Platt • 17 words • 0.0% coverageWriter's voice • 44 words • 0.0% coverageRobert Platt • 10 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageRobert Platt • 10 words • 0.0% coverageRobert Platt • 36 words • 0.0% coverageRobert Platt • 15 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageSusan Schneider • 27 words • 0.0% coverageSusan Schneider • 19 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageSusan Schneider • 9 words • 0.0% coverageSusan Schneider • 30 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageSusan Schneider • 13 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageSthithpragya Gupta • 19 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageSusan Schneider • 15 words • 0.0% coverage
Selected voice

Robert Platt

58%flagged-word coverage
88 attributed words26% of attributed speech47% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

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