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Boston Dynamics, BTS, and Ballet: The Next Act for Robotics

Boston Dynamics, BTS, and Ballet: The Next Act for Robotics

There’s a scene in Swan Lake where the hunky, crossbow-toting protagonist, Prince Siegfried, loses his swan princess, Odette, in an enchanted forest. Suddenly, he finds himself confronted by dozens of identical ballerina swans. Bedazzled and confused, Siegfried runs uselessly up and down the doppelgänger ranks searching for his betrothed. He is beguiled by the multiplicity of swans and the scale of their shared, robotically precise movements.

By the time Swan Lake premiered in the late 19th century, the princely protagonist’s confusion amidst a slew of synchronous ballerinas was already a trope. Romantic ballets are littered with such moments, but they can be found in more contemporary choreographies as well. The American director Busby Berkeley became famous for films such as 42nd Street that featured dozens of dancers uncannily executing the same movements. In the last few decades, the Rockettes and any number of boy bands have brought similar styles to the stage. And throughout history, military marches, parades, and public demonstrations have brought the strategy to the streets. Choreographing groups so the part moves like the whole is both a technique and a tactic.

It is through this Venn diagram intersection of ballet, boy bands, and battalions that we may consider “Spot’s on It,” the latest dance video from robotics manufacturer Boston Dynamics. The clip, which commemorates the company’s acquisition by the Hyundai Motor Company, features quadrupedal “Spot” robots dancing to “IONIQ: I’m on It,” a track by Hyundai global ambassador and mega-boyband BTS, promoting the company’s niche electric car series. In the video, several Spot robots bop with astonishing synchronicity in a catchy-yet-dystopian minute and 20 seconds.

The video opens with five robots in a line, one behind the other, so that only the front Spot is fully visible. The music starts: a new age-y cadence backed by synth clapping and BTS’ prayer-like intoning of the word “IONIQ.” The robots’ heads rise and blossom with the music, pliably shaping themselves into a wavering star, then a helix, then a floral pose that breathes with the melodic line. Their capacity for robotic exactitude allows otherwise simple gestures (the lift of the head, a 90-degree rotation, the opening of Spot’s “mouth”) to create mirrored complexity across all of the robot performers. “Spot’s on It,” à la Busby Berkeley, makes it difficult to distinguish between the robots, and at times it’s unclear which robot “head” belongs to which robot body.

The choreography, by Monica Thomas, takes advantage of the robots’ ability to move exactly like one another. For the Rockettes, BTS, and in many ballets, individual virtuosity is a function of one’s ability to move undistinguished within a group. The Spot robots, however, are functionally, kinesthetically, and visually identical to one another. Human performers can play at such similitude, but robots fully embody it. It’s Siegfried’s uncanny swan valley amidst a robot ballet.

From a technical perspective, the robots’ capacity for movement variation demonstrates the increasing subtlety of Boston Dynamics’ choreography software, a component of its Spot Software Development Kit (SDK) appropriately called “Choreography.” In it, the robot’s user can select a choreo-robotic movement sequence such as a “bourree”—defined in the SDK as “cross-legged tippy-taps like the ballet move”—and modify its relative velocity, yaw, and stance length. In application across an entire dance, one move, such as the “bourree,” can be inverted, reversed, mirrored, done wide or narrow, fast or slow, with increased or diminished distortion across the group. Thomas’ choreography fully utilizes this capacity to execute all manner of kaleidoscopic effects.

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Such complexity and subtlety marks “Spot’s on It” as a significant departure from previous Boston Dynamics dances. First and foremost, it’s clear this video had a more intense production apparatus behind it: “Spot’s on It” is accompanied by a friendly corporate blog post that, for the first time, narrates how Boston Dynamics deploys choreography in its marketing and engineering processes. It’s also, notably, the first time Thomas is publicly credited as the choreographer of Boston Dynamics’ dances. Her labor in viral videos like “Uptown Spot” and “Do You Love Me?” was rendered practically invisible, so Boston Dynamics’ decision to underline Thomas’ role in this latest video is a substantial shift in posture. Scholar Jessica Rajko has previously pointed out the company’s opaque labor politics and fuzzy rationale for not crediting Thomas, which is in contrast to choreo-robotic researchers like Catie Cuan and Amy Laviers, who clearly foreground dancerly contributions to their work. “Spot’s on It” signals Boston Dynamics’ deepening, complexifying engagement with choreographics.

Even though Boston Dynamics’ dancing robots are currently relegated to the realm of branded spectacle, I am consistently impressed by the company’s choreographic strides. In artists’ hands, these machines are becoming eminently capable of expression through performance. Boston Dynamics is a company that takes dance seriously, and, per its blog post, uses choreography as “a form of highly accelerated lifecycle testing for the hardware.” All this dancing is meant to be fun and functional.

The World Needs Deepfake Experts to Stem This Chaos

The World Needs Deepfake Experts to Stem This Chaos

Recently the military coup government in Myanmar added serious allegations of corruption to a set of existing spurious cases against Burmese leader Aung San Suu Kyi. These new charges build on the statements of a prominent detained politician that were first released in a March video that many in Myanmar suspected of being a deepfake.

In the video, the political prisoner’s voice and face appear distorted and unnatural as he makes a detailed claim about providing gold and cash to Aung San Suu Kyi. Social media users and journalists in Myanmar immediately questioned whether the statement was real. This incident illustrates a problem that will only get worse. As real deepfakes get better, the willingness of people to dismiss real footage as a deepfake increases. What tools and skills will be available to investigate both types of claims, and who will use them?

In the video, Phyo Min Thein, the former chief minister of Myanmar’s largest city, Yangon, sits in a bare room, apparently reading from a statement. His speaking sounds odd and not like his normal voice, his face is static, and in the poor-quality version that first circulated, his lips look out of sync with his words. Seemingly everyone wanted to believe it was a fake. Screen-shotted results from an online deepfake detector spread rapidly, showing a red box around the politician’s face and an assertion with 90-percent-plus confidence that the confession was a deepfake. Burmese journalists lacked the forensic skills to make a judgement. Past state and present military actions reinforced cause for suspicion. Government spokespeople have shared staged images targeting the Rohingya ethnic group while military coup organizers have denied that social media evidence of their killings could be real.

But was the prisoner’s “confession” really a deepfake? Along with deepfake researcher Henry Ajder, I consulted deepfake creators and media forensics specialists. Some noted that the video was sufficiently low-quality that the mouth glitches people saw were as likely to be artifacts from compression as evidence of deepfakery. Detection algorithms are also unreliable on low-quality compressed video. His unnatural-sounding voice could be a result of reading a script under extreme pressure. If it is a fake, it’s a very good one, because his throat and chest move at key moments in sync with words. The researchers and makers were generally skeptical that it was a deepfake, though not certain. At this point it is more likely to be what human rights activists like myself are familiar with: a coerced or forced confession on camera. Additionally, the substance of the allegations should not be trusted given the circumstances of the military coup unless there is a legitimate judicial process.

Why does this matter? Regardless of whether the video is a forced confession or a deepfake, the results are most likely the same: words digitally or physically compelled out of a prisoner’s mouth by a coup d’état government. However, while the usage of deepfakes to create nonconsensual sexual images currently far outstrips political instances, deepfake and synthetic media technology is rapidly improving, proliferating, and commercializing, expanding the potential for harmful uses. The case in Myanmar demonstrates the growing gap between the capabilities to make deepfakes, the opportunities to claim a real video is a deepfake, and our ability to challenge that.

It also illustrates the challenges of having the public rely on free online detectors without understanding the strengths and limitations of detection or how to second-guess a misleading result. Deepfakes detection is still an emerging technology, and a detection tool applicable to one approach often does not work on another. We must also be wary of counter-forensics—where someone deliberately takes steps to confuse a detection approach. And it’s not always possible to know which detection tools to trust.

How do we avoid conflicts and crises around the world being blindsided by deepfakes and supposed deepfakes?

We should not be turning ordinary people into deepfake spotters, parsing the pixels to discern truth from falsehood. Most people will do better relying on simpler approaches to media literacy, such as the SIFT method, that emphasize checking other sources or tracing the original context of videos. In fact, encouraging people to be amateur forensics experts can send people down the conspiracy rabbit hole of distrust in images.

Dumbed Down AI Rhetoric Harms Everyone

Dumbed Down AI Rhetoric Harms Everyone

When the European Union Commission released its regulatory proposal on artificial intelligence last month, much of the US policy community celebrated. Their praise was at least partly grounded in truth: The world’s most powerful democratic states haven’t sufficiently regulated AI and other emerging tech, and the document marked something of a step forward. Mostly, though, the proposal and responses to it underscore democracies’ confusing rhetoric on AI.

Over the past decade, high-level stated goals about regulating AI have often conflicted with the specifics of regulatory proposals, and what end-states should look like aren’t well-articulated in either case. Coherent and meaningful progress on developing internationally attractive democratic AI regulation, even as that may vary from country to country, begins with resolving the discourse’s many contradictions and unsubtle characterizations.

The EU Commission has touted its proposal as an AI regulation landmark. Executive vice president Margrethe Vestager said upon its release, “We think that this is urgent. We are the first on this planet to suggest this legal framework.” Thierry Breton, another commissioner, said the proposals “aim to strengthen Europe’s position as a global hub of excellence in AI from the lab to the market, ensure that AI in Europe respects our values and rules, and harness the potential of AI for industrial use.”

This is certainly better than many national governments, especially the US, stagnating on rules of the road for the companies, government agencies, and other institutions. AI is already widely used in the EU despite minimal oversight and accountability, whether for surveillance in Athens or operating buses in Málaga, Spain.

But to cast the EU’s regulation as “leading” simply because it’s first only masks the proposal’s many issues. This kind of rhetorical leap is one of the first challenges at hand with democratic AI strategy.

Of the many “specifics” in the 108-page proposal, its approach to regulating facial recognition is especially consequential. “The use of AI systems for ‘real-time’ remote biometric identification of natural persons in publicly accessible spaces for the purpose of law enforcement,” it reads, “is considered particularly intrusive in the rights and freedoms of the concerned persons,” as it can affect private life, “evoke a feeling of constant surveillance,” and “indirectly dissuade the exercise of the freedom of assembly and other fundamental rights.” At first glance, these words may signal alignment with the concerns of many activists and technology ethicists on the harms facial recognition can inflict on marginalized communities and grave mass-surveillance risks.

The commission then states, “The use of those systems for the purpose of law enforcement should therefore be prohibited.” However, it would allow exceptions in “three exhaustively listed and narrowly defined situations.” This is where the loopholes come into play.

The exceptions include situations that “involve the search for potential victims of crime, including missing children; certain threats to the life or physical safety of natural persons or of a terrorist attack; and the detection, localization, identification or prosecution of perpetrators or suspects of the criminal offenses.” This language, for all that the scenarios are described as “narrowly defined,” offers myriad justifications for law enforcement to deploy facial recognition as it wishes. Permitting its use in the “identification” of “perpetrators or suspects” of criminal offenses, for example, would allow precisely the kind of discriminatory uses of often racist and sexist facial-recognition algorithms that activists have long warned about.

The EU’s privacy watchdog, the European Data Protection Supervisor, quickly pounced on this. “A stricter approach is necessary given that remote biometric identification, where AI may contribute to unprecedented developments, presents extremely high risks of deep and non-democratic intrusion into individuals’ private lives,” the EDPS statement read. Sarah Chander from the nonprofit organization European Digital Rights described the proposal to the Verge as “a veneer of fundamental rights protection.” Others have noted how these exceptions mirror legislation in the US that on the surface appears to restrict facial recognition use but in fact has many broad carve-outs.

Humans Need to Create Interspecies Money to Save the Planet

Humans Need to Create Interspecies Money to Save the Planet

A new form of digital currency for animals, trees, and other wildlife (no, not like Dogecoin) would help protect biodiversity and bend technology back to nature.