At the end of March, the Italian Data Protection Authority (the "Garante"), announced that OpenAI's fancy new ChatGPT software would imminently be blocked from use within the European nation over concerns that ChatGPT's training and function violate the EU's General Data Protection Regulation (GDPR). On Wednesday, the Garante published a list of necessary steps OpenAI will have to take by the end of April if Italy is to lift its temporary limitation on the processing of its user data.

"OpenAI will have to draft and make available, on its website, an information notice describing the arrangements and logic of the data processing required for the operation of ChatGPT along with the rights afforded to data subjects," the Garante announced. Additionally, Italian users must be shown said notice and will have to declare that they are over the age of 18 prior to the completion of their registrations. What's more, the company will be required to age gate the site to filter out users under the age of 18 by the end of September. 

The Garante is also demanding that the company enact "easily accessible tools to allow non-users to exercise their right to object to the processing of their personal data," per Wednesday's release. "The same right will have to be afforded to users if legitimate interest is chosen as the legal basis for processing their data."

Finally, OpenAI must by May, 31st run "through radio, TV, newspapers and the Internet" an ad campaign informing the public about their data collection methods and how Italians' personal information will be used to train the company's algorithms. In all, OpenAI has just 18 days to get all of its regulatory ducks in a row before the regulator implements additional penalties.

It's never been about safety as much as it has control, serving and protecting only to the benefit of the status quo. Clearview AI, PredPol, Shotspotter, they're all Carolyn Bryant Donham's testimony behind a veneer of technological validity — a shiny black box to dazzle the masses while giving the police yet another excuse to fatally bungle their search warrants. In More than a Glitch, data journalist and New York University Associate Professor of Journalism Dr. Meredith Broussard, explores how and why we thought automating aspects of already racially-skewed legal, banking, and social systems would be a good idea. From facial recognition tech that doesn't work on dark-skinned folks to mortgage approval algorithms that don't work for dark-skinned folks, Broussard points to a dishearteningly broad array of initiatives that done more harm than good, regardless of their intention. In the excerpt below, Dr. Broussard looks at America's technochauavnistic history of predictive policing. 

MIT Press

Excerpted from More than a Glitch: Confronting Race, Gender, and Ability Bias by Meredith Broussard. Reprinted with permission from The MIT Press. Copyright 2023.

Predictive policing comes from the “broken windows” era of policing and is usually credited to William Bratton, former New York City police commissioner and LAPD chief. As NYC police commissioner, Bratton launched CompStat, which is perhaps the best-known example of data-driven policing because it appeared as an antagonist called “Comstat” on season three of HBO’s The Wire. “CompStat, a management model linking crime and enforcement statistics, is multifaceted: it serves as a crime control strategy, a personnel performance and accountability metric, and a resource management tool,” writes sociologist Sarah Brayne in her book Predict and Surveil. “Crime data is collected in real time, then mapped and analyzed in preparation for weekly crime control strategy meetings between police executives and precinct commanders.” CompStat was widely adopted by police forces in major American cities in the 1990s and 2000s. By relying heavily on crime statistics as a performance metric, the CompStat era trained police and bureaucrats to prioritize quantification over accountability. Additionally, the weekly meetings about crime statistics served as rituals of quantification that led the participants to believe in the numbers in a way that created collective solidarity and fostered what organizational behaviorists Melissa Mazmanian and Christine Beckman call “an underlying belief in the objective authority of numbers to motivate action, assess success, and drive continuous organizational growth.” In other words: technochauvinism became the culture inside departments that adopted CompStat and other such systems. Organizational processes and controls became oriented around numbers that were believed to be “objective” and “neutral.” This paved the way for the adoption of AI and computer models to intensify policing—and intensify surveillance and harassment in communities that were already over-policed.

Computer models are only the latest trend in a long history of people imagining that software applied to crime will make us safer. In Black Software, Charlton McIlwain traced the history of police imagining that software equals salvation as far back as the 1960s, the dawn of the computational era. Back then, Thomas J. Watson, Jr., the head of IBM, was trying to popularize computers so more people would buy them. Watson had also committed (financially and existentially) to the War on Poverty declared by President Lyndon Johnson upon his election in 1964. “Watson searched for opportunities to be relevant,” McIlwain writes. “He said he wanted to help address the social ills that plagued society, particularly the plight of America’s urban poor... He didn’t know what he was doing.”6 Watson wanted to sell computers and software, so he offered his company’s computational expertise for an area that he knew nothing about, in order to solve a social problem that he didn’t understand using tools that the social problem experts didn’t understand. He succeeded, and it set up a dynamic between Big Tech and policing that still persists. Software firms like Palantir, Clearview AI, and PredPol create biased targeting software that they label “predictive policing,” as if it were a positive innovation. They convince police departments to spend taxpayer dollars on biased software that ends up making citizens’ lives worse. In the previous chapter, we saw how facial recognition technology leads police to persecute innocent people after a crime has been committed. Predictive policing technology leads police to pursue innocent people before a crime even takes place.

It’s trIcky to write about specific policing software because what Chicago’s police department does is not exactly the same as what LAPD or NYPD does. It is hard to say exactly what is happening in each police agency because the technology is changing constantly and is being deployed in different ways. The exact specifications tend to be buried in vendor contracts. Even if a police department buys software, it is not necessarily being used, nor is it being used in precisely the way it was intended. Context matters, and so does the exact implementation of technology, as well as the people who use it. Consider license plate readers, which are used to collect tolls or to conduct surveillance. Automated license plate readers used by a state transportation authority to automatically collect tolls is probably an acceptable use of AI and automated license plate reader technology—if the data is not stored for a long time. The same license plate reader tech used by police as part of dragnet surveillance, with data stored indefinitely, is problematic.

Every time the public has become aware of some predictive policing measure, controversy has erupted. Consider the person-based predictive policing enacted by the Pasco County Sheriff’s Office in Florida, which created a watchlist of people it considered future criminals. Tampa Bay Times reporters Kathleen McGrory and Neil Bedi won a Pulitzer for their story about how the Pasco County Sheriff’s Office generated lists of people it considered likely to break the law. The list was compiled by using data on arrest histories and unspecified intelligence, coupled with arbitrary decisions by police analysts. The sheriff’s department sent deputies to monitor and harass the people on the watchlist. Often, the deputies lacked probable cause, search warrants, or evidence of a crime. In five years, almost 1,000 people were caught up in the systematic harassment labeled “Intelligence-Led Policing.” Notably, a large percentage of the people on the watchlist were BIPOC.

The Pasco program started in 2011, shortly after Chris Nocco took office as sheriff. Nocco came up with the idea to “reform” the department with data-driven initiatives. “For 10 years, nobody really understood how this worked, and the public wasn’t aware of what was going on,” said Bedi, explaining the reporting project.8 The sheriff built a “controversial data-driven approach to policing. He also built a wide circle of powerful friends,” including local and national politicians, who didn’t question his actions.

The harassment didn’t stop there, however. Separately, the Sheriff’s Office created a list of schoolchildren it considered likely to become future criminals. The office gathered data from local schools, including protected information like children’s grades, school attendance records, and child welfare histories. Parents and teachers were not told that children were designated as future criminals, nor did they understand that the students’ private data was being weaponized. The school system’s superintendent initially didn’t realize the police had access to student data, said Kathleen McGrory.

Once the investigation was published, civil liberties groups denounced the intelligence programs. Thirty groups formed a coalition to protest, and four of the targeted people brought lawsuits against the agency. Two bills were proposed to prevent this kind of invasion and misuse in the future. The federal Department of Education opened an investigation into the data sharing between the Sheriff’s Office and the local school district. Fortunately, as a result, police analysts will no longer have access to student grades.

Many people imagine that using more technology will make things “fairer.” This is behind the idea of using machines instead of judges, an idea that surfaces periodically among lawyers and computer scientists. We see it in the adoption of body-worn cameras, an initiative that has been growing since LAPD officers brutally assaulted Rodney King in 1991 and the attack was captured on a home camcorder. There’s an imaginary world where everything is captured on video, there are perfectly fair and objective algorithms that adjudicate what happens in the video feed, facial recognition identifies bad actors, and the heroic police officers go in and save the day and capture the bad guys. This fantasy is taken to its logical conclusion in the film Minority Report, where Tom Cruise plays a police officer who arrests people before they commit crimes, on the recommendation of some teenagers with precognition who are held captive in a swimming pool full of goo. “It’s just like Minority Report,” a police officer marveled to sociologist Sarah Brayne, when the two were discussing Palantir’s policing software.

What makes this situation additionally difficult is the fact that many of the people involved in the chain are not malevolent. For example, my cousin, who is white, was a state police officer for years. He’s wonderful and kind and honest and upstanding and exactly the person I would call on if I were in trouble. He and his family are very dear to me and I to them. I believe in the law, and I believe in law enforcement in the abstract, in the way that many people do when they have the privilege of not interacting with or being targeted by law enforcement or the courts.

But the origins of policing are problematic for Black people like me, and the frequency of egregious abuses by police is out of control in today’s United States. Police technology and machine fairness are the reasons why we need to pause and fix the human system before implementing any kind of digital system in policing.

The current system of policing in the United States, with the Fraternal Order of Police and the uniforms and so on, began in South Carolina. Specifically, it emerged in the 1700s in Charleston, South Carolina, as a slave patrol. “It was quite literally a professional force of white free people who came together to maintain social control of black, enslaved people living inside the city of Charleston,” said ACLU Policing Policy Director Paige Fernandez in a 2021 podcast. “They came together for the sole purpose of ensuring that enslaved black people did not organize and revolt and push back on slavery. That is the first example of a modern police department in the United States.” In her book Dark Matters: Surveillance of Blackness, scholar Simone Brown connects modern surveillance of Black bodies to chattel slavery via lantern laws, which were eighteenth-century laws in New York City requiring Black or mixed-race people to carry a lantern if out at night unaccompanied by a white person. Scholar Josh Scannell sees lantern laws as the precedent for today’s policy of police using floodlights to illuminate high-crime areas all night long. People who live in heavily policed neighborhoods never get the peaceful cloak of darkness, as floodlights make it artificially light all night long and the loud drone of the generators for the lights makes the neighborhood noisier.

The ACLU’s Fernandez draws a line from slave patrols maintaining control over Black people to the development of police departments to the implementation of Jim Crow–era rules and laws to police enforcing segregation during the civil rights era and inciting violence against peaceful protestors to escalating police violence against Black and Brown people and leading to the Black Lives Matter movement. Fernandez points out that the police tear-gassed and pepper-sprayed peaceful protestors in the summer of 2020, fired rubber bullets at protestors, charged at protestors, and used techniques like kettling to corner protestors into closed spaces where violence could be inflicted more easily.

The statistics paint a grim picture. “Black people are 3.5 times more likely than white people to be killed by police when Blacks are not attacking or do not have a weapon. George Floyd is an example,” writes sociologist Rashawn Ray in a 2020 Brookings Institute policy brief about police accountability.14 “Black teenagers are 21 times more likely than white teenagers to be killed by police. That’s Tamir Rice and Antwon Rose. A Black person is killed about every 40 hours in the United States. That’s Jonathan Ferrell and Korryn Gaines. One out of every one thousand Black men can expect to be killed by police violence over the life course. This is Tamir Rice and Philando Castile.” When Derek Chauvin, the police officer who killed George Floyd, was found guilty, it was remarkable because police are so rarely held accountable for violence against Black and Brown bodies.

Reform is needed. That reform, however, will not be found in machines.

Our reverence towards stars and celebrities was not borne of the 19th century’s cinematic revolution, but rather has been a resilient aspect of our culture for millennia. Ancient tales of immortal gods rising again and again after fatal injury, the veneration and deification of social and political leaders, Madame Tussauds’ wax museums and the Academy Awards’ annual In Memoriam segment, they’re are all facets of the human compulsion to put well-known thought leaders, tastemakers and trendsetters up on pedestals. And with a new, startlingly lifelike generation of generative artificial intelligence (gen-AI) at our disposal, today’s celebrities could potentially remain with us long after their natural deaths. Like ghosts, but still on TV, touting Bitcoin and Metaverse apps. Probably.

Fame is the name of the game

American Historian Daniel Boorstin once quipped, “to be famous is to be well known for being well-known.” With the rise of social media, achieving celebrity is now easier than ever, for better or worse.

“Whereas stars are often associated with a kind of meritocracy,” Dr. Claire Sisco King, Associate Professor of Communication Studies and Chair of the Cinema and Media Arts program at Vanderbilt. “Celebrity can be acquired through all kinds of means, and of course, the advent of digital media has, in many ways, changed the contours of celebrity because so-called ordinary people can achieve fame in ways that were not accessible to them prior to social media.”

What’s more, social media provides an unprecedented degree of access and intimacy between a celebrity and their fans, even at the peak of the paparazzi era. “We develop these imagined intimacies with celebrities and think about them as friends and loved ones,” King continued. “I think that those kinds of relationships illustrate the longing that people have for senses of connectedness and interrelatedness.”

For as vapid as the modern celebrity existence is portrayed in popular media, famous people have long served important roles in society as trend-setters and cultural guides. During the Victorian era, for example, British folks would wear miniature portraits of Queen Victoria to signal their fealty and her choice to wear a white wedding gown in 1840 is what started the modern tradition. In the US, that manifests with celebrities as personifications of the American Dream — each and every single one having pulled themselves up by the bootstraps and sworn off avocado toast to achieve greatness, despite their humble beginnings presumably in a suburban garage of some sort.

“The narratives that we return to, “ King said, “can become comforts for making sense of that inevitable part of the human experience: our finiteness.” But what if our cultural heroes didn’t die? At least not entirely? What if, even after Tom Hanks shuffles off this mortal coil, his likeness and personality were digitally preserved in perpetuity? We’re already sending long-dead recording artists like Roy Orbison, Tupac Shakur and Whitney Houston back out on tour as holographic performers. The Large Language Models (LLMs) that power popular chatbots like ChatGPT, Bing Chat, and Bard, are already capable of mimicking the writing styles of whichever authors they’ve been trained on. What’s to stop us from smashing these technologies together into an interactive Tucker-Dolcetto amalgamation of synthesized content? Turns out, not much beyond the threat of a bad news cycle.

How to build a 21st century puppet

Cheating death has been an aspirational goal of humanity since prehistory. The themes of resurrection, youthful preservation and outright immortality are common tropes throughout our collective imagination — notions that have founded religions, instigated wars, and launched billion dollar beauty and skin care empires. If a society’s elites weren’t mummifying themselves ahead of a glorious afterlife, bits and pieces of their bodies and possessions were collected and revered as holy relics, cultural artifacts to be cherished and treasured as a physical connection to the great figures and deeds of yore.

Technological advances since the Middle Ages have, thankfully, by and large eliminated the need to carry desiccated bits of your heroes in a coat pocket. Today, fans can connect with their favorite celebrities — whether still alive or long-since passed — through the star’s available catalog of work. For example, you can watch Robin Williams’ movies, stand up specials, Mork and Mindy, and read his books arguably more easily now than when he was alive. Nobody’s toting scraps of hallowed rainbow suspender when they can rent Jumanji from YouTube on their phone for $2.99. It’s equally true for William Shakespeare, whose collected works you can read on a Kindle as you wait in line at the DMV.

At this point, it doesn’t really matter how long a beloved celebrity has been gone — so long as sufficiently large archives of their work remain, digital avatars can be constructed in their stead using today’s projection technologies, generative AI systems, and deepfake audio/video. Take the recent fad of deceased singers and entertainers “going back out on tour” as holographic projections of themselves for example.

The projection systems developed by BASE Hologram and the now-defunct HologramUSA, which made headlines in the middle of the last decade for their spectral representations of famously deceased celebrities, used a well-known projection effect known as Pepper’s Ghost. Developed in the early 19th century by British inventor John Henry Pepper, the image of an off-stage performer is reflected onto a transparent sheet of glass interposed between the stage and audience to produce a translucent, ethereal effect ideal for depicting the untethered spirits that routinely haunted theatrical protagonists at the time.

Public Domain - Wikipedia

Turns out, the technique works just as well with high-definition video feeds and LED light sources as it did with people wiggling in bedsheets by candlelight. The modern equivalent is called the "Musion Eyeliner" and rather than a transparent sheet of glass, it uses a thin metalized film set at a 45 degree angle towards the audience. It’s how the Gorillaz played “live” at the 2006 Grammy Awards and how Tupac posthumously performed at Coachella in 2012, but the technology is limited by the size of the transparent sheet. If we’re ever going to get the Jaws 19 signage Back to the Future II promised us, we’re likely going to use arrays of fan projectors like those developed by London-based holographic startup, Hypervsn, to do so.

“Holographic fans are types of displays that produce a 3-dimensional image seemingly floating in the air using the principle of POV (Persistence of Vision), using strips of RGB LEDs attached to the blades of the fan and a control-unit lighting up the pixels,” Dr Priya C, Associate Professor at Sri Sairam Engineering College, and team wrote in a 2020 study on the technology. “As the fan rotates, the display produces a full picture.”

Dr Priya C goes on to say “Generally complex data can be interpreted more effectively when displayed in three dimensions. In the information display industry, three dimensional (3D) imaging, display, and visualization are therefore considered to be one of the key technology developments that will enter our daily life in the near future.”

“From a technical standpoint, the size [of a display] is just a matter of how many devices you are using and how you actually combine them,” Hypervsn Lead Product Manager, Anastasia Sheluto, told Engadget. “The biggest wall we have ever considered was around 400 devices, that was actually a facade of one building. A wall of 12 or 15 [projectors] will get you up to 4k resolution.” While the fan arrays need to be enclosed to protect them from the elements and the rest of us from getting whacked by a piece of plastic revolving at a few thousand RPMs, these displays are already finding use in museums and malls, trade shows and industry showcases.

What’s more, these projector systems are rapidly gaining streaming capabilities, allowing them to project live interactions rather than merely pre-recorded messages. Finally, Steven Van Zandt’s avatar in the ARHT Media Holographic Cube at Newark International will do more than stare like he’s not mad, just disappointed, and the digital TSA assistants of tomorrow may do more than repeat rote instructions for passing travelers as the human ones do today.

Getting Avatar Van Zandt to sound like the man it’s based on is no longer much of a difficult feat either. Advances in the field of deepfake audio, more formally known as speech synthesis, and text-to-speech AI, such as Amazon Polly or Speech Services by Google, have led to a commercialization of synthesized celebrity voice overs.

Where once a choice between Morgan Freeman and Darth Vader reading our TomTom directions was considered bleeding-edge cool, today, companies like Speechify offer voice models from Snoop Dogg, Gwyneth Paltrow, and other celebs who (or whose estates) have licensed their voice models for use. Even recording artists who haven’t given express permission for their voices to be used are finding deep fakes of their work popping up across the internet.

In Speechify’s case at least, “our celebrity voices are strictly limited to personal consumption and exclusively part of our non-commercial text-to-speech (TTS) reader,” Tyler Weitzman, Speechify Co-Founder and Head of AI, told Engadget via email. “They're not part of our Voice Over Studio. If a customer wants to turn their own voice into a synthetic AI voice for their own use, we're open to conversations.”

“Text-to-speech is one of the most important technologies in the world to advance humanity,” Weitzman continued. “[It] has the potential to dramatically increase literacy rates, spread human knowledge, and break cultural barriers.”

ElevenLabs’ Prime Voice AI software similarly can recreate near perfect vocal clones from uploaded voice samples — the entry level Instant Voice Cloning service only requires around a minute of audio but doesn’t utilize actual AI model training (limiting its range of speech) and an enterprise version that can only be accessed after showing proof that the voice they’re cloning is licensed for that specific use. What’s more, “Cloning features are limited to paid accounts so if any content created using ElevenLabs is shared or used in a way that contravenes the law, we can help trace it back to the content creator,” ElevenLabs added.

The Enterprise-grade service also requires nearly 3 hours of input data to properly train the language model but company reps assure Engadget that, “the results are almost indistinguishable from the original person’s voice.” Surely Steve Van Zandt was onscreen for that long over the course of Lillyhammer’s four-season run.

Unfortunately, the current need for expansive, preferably high-quality, audio recordings on which to train an AI TTS model severely limits which celebrity personalities we’d be able to bring back. Stars and public figures from the second half of the 20th century would obviously have far more chance of having three hours of tape available for training than, say, Presidents Jefferson or Lincoln. Sure, a user could conceivably reverse engineer a voiceprint from historical records — ElevenLabs Voice Design allows users to generate unique voices with adjustable qualities like age, gender, or accent — and potentially recreate Theodore Roosevelt’s signature squeaky sound, but it’ll never be quite the same as hearing the 26th President himself.

Providing something for the synthesized voices to say is proving to be a significant challenge — at least providing something historically accurate, as the GPT-3-powered iOS app, Historical Figures Chat has shown. Riding the excitement around ChatGPT, the app was billed as able to impersonate any of 20,000 famous folks from the annals of history. Despite its viral popularity in January, the app has been criticized by historians for returning numerous factual and characteristic inaccuracies from its figure models. Genocidal Cambodian dictator, Pol Pot, at no point in his reign showed remorse for his nation’s Killing Fields, nor did Nazi general and Holocaust architect, Heinrich Himmler, but even gentle prodding was enough to have their digital recreations begin spouting mea culpas.

“It’s as if all of the ghosts of all of these people have hired the same PR consultants and are parroting the same PR nonsense,” Zane Cooper, a researcher at the University of Pennsylvania, remarked to the Washington Post.

We can, but should we?

Accuracy issues aren’t the only challenges generative AI “ghosts” currently face, as apparently, even death itself will not save us from copyright and trademark litigation. “There's already a lot of issues emerging,” Dan Schwartz, partner and IP trial lawyer at Nixon Peabody, told Engadget. “Especially for things like ChatGPT and generative AI tools, there will be questions regarding ownership of any intellectual property on the resulting output.

“Whether it's artwork, whether it's a journalistic piece, whether it's a literary piece, whether it is an academic piece, there will be issues over the ownership of what comes out of that,” he continued. “That issue has really yet to be defined and I think we're still a ways away from intellectual property laws fully having an opportunity to address it. I think these technologies have to percolate and develop a little bit and there will be some growing pains before we get to meaningful regulation on them.”

The US Copyright Office in March announced that AI-generated art cannot be copyrighted by the user under US law, equating the act of prompting the computer to produce a desired output with asking a human artist the same. "When an AI technology receives solely a prompt from a human and produces complex written, visual, or musical works in response, the 'traditional elements of authorship' are determined and executed by the technology — not the human user," the office stated.

This is the opposite of the stance taken by a Federal Appeals Court. “[Patent law regarding AI] for the most part, is pretty well settled here in the US,” Schwartz said, “that an AI system cannot be an inventor of a new, patentable invention. It's got to be a human, so that will impact how people apply for patents that come out of generative AI tools.”

Output-based infringement aside, the training methods used by firms like OpenAI and Stability AI, which rely on trawling the public web for data with which to teach their models, have proven problematic as well, having repeatedly caught lawsuits for getting handsy with other people’s licensed artwork. What’s more, generative AI has already shown tremendous capacity and capability in creating illegal content. Deepfake porn ads featuring the synthetic likenesses of Emma Watson and Scarlett Johansson ran on Facebook for more than two days in March before being flagged and removed, for example.

Until the wheels of government can turn enough to catch up to these emerging technologies, we’ll have to rely on market forces to keep companies from disrupting the rest of us back into the stone age. So far, such forces have proved quick and efficient. When Google’s new Bard system immediately (but confidently) fumbled basic facts about the James Webb Space Telescope, that little whoopsie-doodle immediately wiped $100 billion off the company’s stock value. The Historical Figures Chat app, similarly, is no longer available for download on the App Store, despite reportedly receiving multiple investment offers in January. It has since been replaced with numerous, similarly-named clone apps.

“I think what is better for society is to have a system of liability in place so that people understand what the risks are,” Schwartz argued. “So that if you put something out there that creates racist, homophobic, anti-any protected class, inappropriate content, whoever’s responsible for making that tool available, will likely end up facing the potential of liability. And I think that's going to be pretty well played out over the course of the next year or two.”

Celebrity as an American industry

While the term “celebrity” has been around since being coined in 17th century France, during the days of John Jacques Rousseau, it was the Americans in the 20th century who first built the concept into a commercial enterprise.

By the late 1920s, with the advent of Talkies, the auxiliary industry of fandom was already in full swing. “You [had] fan magazines like Motion Picture, Story Magazine or Photoplay that would have pictures of celebrities on the cover, have stories about celebrities behind the scenes, stories about what happened on the film set,” King explained. “So, as the film industry develops alongside this, you start to get Hollywood Studios.” And with Hollywood Studios came the star system.

“Celebrity has always been about manufacturing images, creating stories,” King said. The star system existed in the 1930s and ‘40s and did to young actors and actrices what Crypton Future Media did to Hatsune Miku: it assembled them into products, constructing synthetic personalities for them from the ground up.

Actors, along with screenwriters, directors and studio executives of the era, would coordinate to craft specific personas for their stars. “You have the ingénue or the bombshell,” King said. “The studios worked really closely with fan magazines, with their own publicity arms and with gossip columnist to tell very calculated stories about who the actors were.” This diverted focus from the film itself and placed it squarely on the constructed, steerable, personas crafted by the studio — another mask for actors to wear, publicly and even after the cameras were turned off.

“Celebrity has existed for centuries and the way it exists now is not fundamentally different from how it used to be,” King added. “But it has been really amplified, intensified and made more ubiquitous because of changing industry and technological norms that have developed in the 20th and 21st centuries.”

Even after Tom Hanks is dead, Tom Hanks Prime will live forever

Between the breakneck pace of technological advancement with generative AI (including deepfake audio and video), the promise of future “touchable” plasma displays offering hard light-style tactile feedback through femtosecond laser bursts, and Silicon Valley’s gleeful disregard towards the negative public costs borne from their “disruptive” ideas, the arrival of immortal digitized celebrities hawking eczema creams and comforting lies during commercial breaks is now far more likely a matter of when, rather than if.

But what does that mean for celebrities who are still alive? How will knowing that even after the ravages of time take Tom Hanks from us, that at least a lightly interactable likeness might continue to exist digitally? Does the visceral knowledge that we’ll never truly be rid of Jimmy Fallon empower us to loathe him even more?

“This notion of the simulacra of the celebrity, again, is not entirely new,” King explained. “We can point to something like the Madame Tussaud's wax museum, which is an attempt to give us a version of the celebrity, there are impersonators who dress and perform as them, so I think that people take a certain kind of pleasure in having access to an approximation of the celebrity. But that experience never fully lives up.”

“If you go and visit the Mona Lisa in the Louvre, there's a kind of aura [to the space],” she continued. “There's something intangible, almost magical about experiencing that work of art in person versus seeing a print of it on a poster or on a museum tote bag or, you know, coffee mug that it loses some of its kind of ineffable quality.”

"Birds fly South for the winter and North for the summer," has historically proven to be only slightly less reliable a maxim than the sun always rising in the East and setting in the West. Humanity has been fascinated by the comings and goings of our avian neighbors for millennia, but the why's and how's of their transitory travel habits have remained largely a mystery until recent years. In Flight Paths, science author Rebecca Heisman details the fascinating history of modern bird migration research and the pioneering ornithologists that helped the field take off. In the excerpt below, Heisman recalls the efforts of Dr. Bill Cochran, a trailblazer in radio-tagging techniques, to track his airborne, and actively-transmitting, quarry across the Canadian border.        

HarperCollins

From Flight Paths, Copyright © 2023 By Rebecca Heisman. Reprinted here with permission of Harper, an imprint of HarperCollins Publishers

Follow That Beep

Swainson’s thrush looks a bit like a small brown version of its familiar cousin the American robin. Its gray-brown back contrasts with a pale, spotted chest and pale “spectacle” markings around its eyes. These thrushes are shy birds that forage for insects in the leaf litter on the forest floor, where they blend in with the dappled light and deep shadows. Birders know them by their fluting, upward-spiraling song, which fills the woods of Canada and the northern United States with ethereal music in summer. But they don’t live there year-round; they spend the winters in Mexico and northern South America, then return north to breed.

On the morning of May 13, 1973, a Swainson’s thrush pausing on its journey from its winter home to its summer home blundered into a mist net in east-central Illinois. The researchers who gently pulled it from the net went through all the usual rituals—weighing and measuring it, clasping a numbered metal band around its leg—but they added one unusual element: a tiny radio transmitter weighing just five- thousandths of an ounce. They carefully trimmed the feathers from a small patch on the bird’s back, then used eyelash glue to cement the transmitter, mounted on a bit of cloth, in place against the bird’s skin (Generations of ornithologists have learned exactly where to find the eyelash glue at their local cosmetics store. Designed to not irritate the delicate skin of the eyelids when attaching false eyelashes, it doesn’t irritate birds’ skin, either, and wears off after weeks or months.) 

When the thrush was released, it probably shuffled its feathers a few times as it got used to its new accessory, then returned to resting and foraging in preparation for continuing its trek. At only around 3 percent of the bird’s total body weight, the transmitter wouldn’t have impeded the bird noticeably as it went about its daily routine. Then, around 8:40 that evening, after the sun had dipped far enough below the horizon that the evening light was beginning to dim, the thrush launched itself into the air, heading northwest.

It would have had no way of knowing that it was being followed. Bill Cochran — the same engineer who, a decade and a half earlier, had rigged up a tape recorder with a bicycle axle and six thousand feet of tape so that Richard Graber could record a full night of nocturnal flight calls — had been waiting nearby in a converted Chevy station wagon with a large antenna poking out of a hole in the roof. When the thrush set out into the evening sky, Cochran and a student named Charles Welling were following on the roads below.

All they could see in the deepening night was the patch of highway illuminated by their headlights, but the sound of the wavering “beep . . . beep . . . beep” of the transmitter joined them to the thrush overhead as if by an invisible thread. They would keep at it for seven madcap nights, following the thrush for more than 930 miles before losing the signal for good in rural southern Manitoba on the morning of May 20.

Along the way, they would collect data on its altitude (which varied from 210 to 6,500 feet), air and ground speed (eighteen to twenty-seven and nine to fifty-two miles per hour, respectively, with the ground speed depending on the presence of headwinds or tailwinds), distance covered each night (65 to 233 miles), and, crucially, its heading. Because they were able to stick with the bird over such a long distance, Cochran and Welling were able to track how the precise direction the bird set out in each night changed as its position changed relative to magnetic north. The gradual changes they saw in its heading were consistent with the direction of magnetic north, providing some of the first real-world evidence that migrating songbirds use some sort of internal magnetic compass as one of their tools for navigation. Today Bill Cochran is a legend among ornithologists for his pioneering work tracking radio-tagged birds on their migratory odysseys. But it wasn’t birds that first drew him into the field of radio telemetry; it was the space race.

From Sputnik to Ducks

In October 1957, the Soviet Union launched the world’s first artificial satellite into orbit. Essentially just a metal sphere that beeped, Sputnik 1 transmitted a radio signal for three weeks before its battery died. (It burned up in the atmosphere in January 1958.) That signal could be picked up by anyone with a good radio receiver and antenna, and scientists and amateur radio enthusiasts alike tracked its progress around and around Earth.

It caused a sensation around the world — including in Illinois, where the University of Illinois radio astronomer George Swenson started following the signals of Sputnik 1 and its successors to learn more about the properties of Earth’s atmosphere. Around 1960, Swenson got permission to design a radio beacon of his own to be incorporated into a Discoverer satellite, the U.S. answer to the Sputnik program. In need of locals with experience in electrical engineering to work on the project, he recruited Bill Cochran (who still had not officially finished his engineering degree — he wouldn’t complete the last class until 1964) to assist.

Cochran, as you may recall, had spent the late 1950s working at a television station in Illinois while studying engineering on the side and spending his nights helping Richard Graber perfect his system for recording nocturnal flight calls. By 1960, no longer satisfied with flight calls alone as a means of learning about migration, Graber had procured a small radar unit and gotten Cochran a part-time job with the Illinois Natural History Survey helping operate it. But along the way, Cochran had apparently demonstrated “exceptional facility with transistor circuits,” which is what got him the job with Swenson. It was the transistor, invented in 1947, that ultimately made both the space race and wildlife telemetry possible.

The beating heart of a radio transmitter is the oscillator, usually a tiny quartz crystal. When voltage is applied to a crystal, it changes shape ever so slightly at the molecular level and then snaps back, over and over again. This produces a tiny electric signal at a specific frequency, but it needs to be amplified before being sent out into the world. Sort of like how a lever lets you turn a small motion into a bigger one, an amplifier in an electrical circuit turns a weak signal into a stronger one.

Before and during World War II, amplifying a signal required controlling the flow of electrons through a circuit using a series of vacuum-containing glass tubes. Vacuum tubes got the job done, but they were fragile, bulky, required a lot of power, and tended to blow out regularly; owners of early television sets had to be adept at replacing vacuum tubes to keep them working. In a transistor, the old-fashioned vacuum tube is replaced by a “semiconductor” material (originally germanium, and later silicon), allowing the flow of electrons to be adjusted up or down by tweaking the material’s conductivity. Lightweight, efficient, and durable, transistors quickly made vacuum tubes obsolete. Today they’re used in almost every kind of electric circuit. Several billion of them are transisting away inside the laptop I’m using to write this.

As transistors caught on in the 1950s, the U.S. Navy began to take a special interest in radio telemetry, experimenting with systems to collect and transmit real-time data on a jet pilot’s vital signs and to study the effectiveness of cold-water suits for sailors. These efforts directly inspired some of the first uses of telemetry for wildlife research. In 1957, scientists in Antarctica used the system from the cold-water suit tests to monitor the temperature of a penguin egg during incubation, while a group of researchers in Maryland borrowed some ideas from the jet pilot project and surgically implanted transmitters in woodchucks. [ed: Although harnesses, collars, and the like are also commonly used for tracking wildlife today, surgically implanting transmitters has its advantages, such as eliminating the chance that an external transmitter will impede an animal’s movements.] Their device had a range of only about twenty-five yards, but it was the first attempt to use radio telemetry to track animals’ movements. The Office of Naval Research even directly funded some of the first wildlife telemetry experiments; navy officials hoped that radio tracking “may help discover the bird’s secret of migration, which disclosure might, in turn, lead to new concepts for the development of advanced miniaturized navigation and detection systems.”

Cochran didn’t know any of this at the time. Nor did he know that the Discoverer satellites he and Swenson were building radio beacons for were, in fact, the very first U.S. spy satellites; he and Swenson knew only that the satellites’ main purpose was classified. Working with a minimal budget, a ten-pound weight limit, and almost no information about the rocket that would carry their creation, they built a device they dubbed Nora-Alice (a reference to a popular comic strip of the time) that launched in 1961. Cochran was continuing his side job with the Illinois Natural History Survey all the while, and eventually someone there suggested trying to use a radio transmitter to track a duck in flight.

“A mallard duck was sent over from the research station on the Illinois River,” Swenson later wrote in a coda to his reminiscences about the satellite project. “At our Urbana satellite-monitoring station, a tiny transistor oscillator was strapped around the bird’s breast by a metal band. The duck was disoriented from a week’s captivity, and sat calmly on the workbench while its signal was tuned in on the receiver. As it breathed quietly, the metal band periodically distorted and pulled the frequency, causing a varying beat note from the receiver.”

Swenson and Cochran recorded those distortions and variations on a chart, and when the bird was released, they found they could track its respiration and wing beats by the changes in the signal; when the bird breathed faster or beat its wings more frequently, the distortions sped up. Without even meaning to, they’d gathered some of the very first data on the physiology of birds in flight.

An Achievement of Another Kind

Bill Cochran enjoys messing with telemarketers. So, when he received a call from a phone number he didn’t recognize, he answered with a particularly facetious greeting.

“Animal shelter! We’re closed!”

“Uh . . . this is Rebecca Heisman, calling for Bill Cochran?”

“Who?”

“Is this Bill Cochran?”

“Yes, who are you?”

Once we established that he was in fact the radio telemetry legend Bill Cochran, not the animal shelter janitor he was pretending to be, and I was the writer whom he’d invited via email to give him a call, not a telemarketer, he told me he was busy but that I could call him back at the same time the next day.

Cochran was nearly ninety when we first spoke in the spring of 2021. Almost five decades had passed since his 1973 thrush-chasing odyssey, but story after story from the trek came back to him as we talked. He and Welling slept in the truck during the day when the thrush landed to rest and refuel, unwilling to risk a motel in case the bird took off again unexpectedly. While Welling drove, Cochran controlled the antenna. The base of the column that supported it extended down into the backseat of their vehicle, and he could adjust the antenna by raising, lowering, and rotating it, resembling a submarine crewman operating a periscope.

At one point, Cochran recalled, he and Welling got sick with “some kind of flu” while in Minnesota and, unable to find a doctor willing to see two eccentric out-of-towners on zero notice, just “sweated it out” and continued on. At another point during their passage through Minnesota, Welling spent a night in jail. They were pulled over by a small-town cop (Cochran described it as a speed trap but was adamant that they weren’t speeding, claiming the cop was just suspicious of the weird appearance of their tracking vehicle) but couldn’t stop for long or they would lose the bird. Welling stayed with the cop to sort things out while Cochran went on, and after the bird set down for the day, Cochran doubled back to pick him up.

“The bird got a big tailwind when it left Minnesota,” Cochran said. “We could barely keep up, we were driving over the speed limit on those empty roads — there aren’t many people in North Dakota — but we got farther and farther behind it, and finally by the time we caught up with it, it had already flown into Canada.”

Far from an official crossing point where they could legally enter Manitoba, they were forced to listen at the border as the signal faded into the distance. The next day they found a border crossing (heaven knows what the border agents made of the giant antenna on top of the truck) and miraculously picked up the signal again, only to have their vehicle start to break down. “It overheated and it wouldn’t run, so the next thing you know Charles is out there on the hood of the truck, pouring gasoline into the carburetor to keep it running,” Cochran recalled. “And every time we could find any place where there was a ditch with rainwater, we improvised something to carry water out of the ditch and pour it into the radiator. We finally managed to limp into a town to get repairs made.”

Cochran recruited a local pilot to take him up in a plane in one last attempt to relocate the radio-tagged bird and keep going, but to no avail. The chase was over. The data they had collected would be immortalized in a terse three-page scientific paper that doesn’t hint at all the adventures behind the numbers.

That 1973 journey wasn’t the first time Cochran and his colleagues had followed a radio-tagged bird cross-country, nor was it the last. After his first foray into wildlife telemetry at George Swenson’s lab, Cochran quickly became sought after by wildlife biologists throughout the region. He first worked with the Illinois Natural History Survey biologist Rexford Lord, who was looking for a more accurate way to survey the local cottontail rabbit population. Although big engineering firms such as Honeywell had already tried to build radio tracking systems that could be used with wildlife, Cochran succeeded where others had failed by literally thinking outside the box: instead of putting the transmitter components into a metal box that had to be awkwardly strapped to an animal’s back, he favored designs that were as small, simple, and compact as possible, dipping the assembly of components in plastic resin to seal them together and waterproof them. Today, as in Cochran’s time, designing a radio transmitter to be worn by an animal requires making trade-offs among a long list of factors: a longer antenna will give you a stronger signal, and a bigger battery will give you a longer-lasting tag, but both add weight. Cochran was arguably the first engineer to master this balancing act.

The transmitters Cochran created for Lord cost eight dollars to build, weighed a third of an ounce, and had a range of up to two miles. Attaching them to animals via collars or harnesses, Cochran and Lord used them to track the movements of skunks and raccoons as well as rabbits. Cochran didn’t initially realize the significance of what he’d achieved, but when Lord gave a presentation about their project at a 1961 mammalogy conference, he suddenly found himself inundated with job offers from biologists. Sharing his designs with anyone who asked instead of patenting them, he even let biologists stay in his spare room when they visited to learn telemetry techniques from him. When I asked him why he decided to go into a career in wildlife telemetry rather than sticking with satellites, he told me he was simply more interested in birds than in a job “with some engineering company making a big salary and designing weapons that’ll kill people.”

Virgin Orbit’s days of slinging satellites into space aboard aircraft-launched rockets have come to an end Thursday. After six years in business, Virgin’s satellite launch subsidiary has announced via SEC filing that it does not have the funding to continue operations and will be shuttering for “the foreseeable future,” per CNBC. Nearly 90 percent of Virgin Orbit’s employees — 675 people in total — will be laid off immediately.

Virgin Orbit was founded in 2017 for the purpose of developing and commercializing LauncherOne, a satellite launch system fitted under a modified 747 airliner, dubbed Cosmic Girl. The system was designed to put 500 pounds of cubesats into Low Earth Orbit by firing them in a rocket from said airliner flying at an altitude of 30,000 - 50,000 feet. Despite a string of early successes — both in terms of development milestones and expanding service contracts with the UK military, LauncherOne’s first official test in May of 2020 failed to deliver its simulated payload into orbit.

A second attempt the following January in 2022 however was a success with the launch of 10 NASA cube sats into LEO, as was Virgin Orbit’s first commercial satellite launch that June. It successfully sent seven more satellites into orbit in January 2022 and quietly launched Space Force assets that July.

In all, Virgin Orbit made six total flights between 2020 and 2023, only four successfully. The most recent attempt was dubbed the Start Me Up event and was supposed to mark the first commercial space launch from UK soil. Despite the rocket successfully separating from its parent aircraft, an upper stage “anomaly” prevented the rocket’s payload from entering orbit. It was later determined that a $100 fuel filter had failed and resulted in the fault.

As TechCrunch points out, Virgin Group founder, Sir Richard Branson, “threw upwards of $55 million to the sinking space company,” in recent months but Start Me Up’s embarrassing failure turned out to be the final straw. On March 16th, Virgin Orbit announced an “operational pause” and worker furlough for its roughly 750 employees as company leadership scrambled to find new funding sources. The company extended the furlough two weeks later and called it quits on Thursday.

“Unfortunately, we’ve not been able to secure the funding to provide a clear path for this company,” Virgin CEO Dan Hart said in an all-hands call obtained by CNBC. “We have no choice but to implement immediate, dramatic and extremely painful changes.” 

Impacted employees will reportedly receive severance packages, according to Hart, including a cash payment, continued benefits and a “direct pipeline” to Virgin Galactic’s hiring department. Virgin Orbit’s two top executives will also receive “golden parachute” severances which were approved by the company’s board, conveniently, back in mid-March right when the furloughs first took effect.

With extreme weather events regularly flooding our coastal cities and burning out our rural communities, Google in its magnanimity has developed a new set of online tools that civil servants and community organizers alike can use in their efforts to stave off climate change-induced catastrophe.

Google already pushes extreme weather alerts to users in affected locations, providing helpful, easy-to-understand information about the event through the Search page — whether its a winter storm warning, flood advisories, tornado warnings, or what have you. The company has now added extreme heat alerts to that list. Googling details on the event will return everything from the predicted start and end dates of the heatwave to medical issues to be aware of during it and how to mitigate their impacts. The company is partnering with the Global Heat Health Information Network (GHHIN) to ensure that the information provided is both accurate and applicable. 

Google

It's a lot easier to keep the citizenry comfortable in hot weather if the cities themselves aren't sweltering, but our love affair with urban concrete has not been amenable to that goal. That's why Google has developed Tree Canopy, a feature within the company's Environmental Insights Explorer app, which "combines AI and aerial imagery so cities can understand their current tree coverage and better plan urban forestry initiatives," per Wednesday's release.

Tree Canopy is already in use in more than a dozen cities but, with Wednesday's announcement, the program will be drastically expanding, out to nearly 350 cities around the world including Atlanta, Sydney, Lisbon and Paris. Google also offers a similarly-designed AI to help plan the installation of "cool roofs" which reflect heat from the sun rather than absorb it like today's tar paper roofs do.

Humanity took another step towards its Ghost in the Shell future on Tuesday with Microsoft's unveiling of the new Security Copilot AI at its inaugural Microsoft Secure event. The automated enterprise-grade security system is powered by OpenAI's GPT-4, runs on the Azure infrastructure and promises admins the ability "to move at the speed and scale of AI."

Security Copilot is similar to the large language model (LLM) that drives the Bing Copilot feature, but with a training geared heavily towards network security rather than general conversational knowledge and web search optimization. "This security-specific model in turn incorporates a growing set of security-specific skills and is informed by Microsoft’s unique global threat intelligence and more than 65 trillion daily signals," Vasu Jakkal, Corporate Vice President of Microsoft Security, Compliance, Identity, and Management, wrote Tuesday. 

“Just since the pandemic, we’ve seen an incredible proliferation [in corporate hacking incidents],"Jakkal told Bloomberg. For example, “it takes one hour and 12 minutes on average for an attacker to get full access to your inbox once a user has clicked on a phishing link. It used to be months or weeks for someone to get access.”

Security Copilot should serve as a force multiplier for overworked and under-supported network admins, a filed which Microsoft estimates has more than 3 million open positions. "Our cyber-trained model adds a learning system to create and tune new skills," Jakkal explained. "Security Copilot then can help catch what other approaches might miss and augment an analyst’s work. In a typical incident, this boost translates into gains in the quality of detection, speed of response and ability to strengthen security posture." 

Jakkal anticipates these new capabilities enabling Copilot-assisted admins to respond within minutes to emerging security threats, rather than days or weeks after the exploit is discovered. Being a brand new, untested AI system, Security Copilot is not meant to operate fully autonomously, a human admin needs to remain in the loop. “This is going to be a learning system,” she said. “It’s also a paradigm shift: Now humans become the verifiers, and AI is giving us the data.”

To more fully protect the sensitive trade secrets and internal business documents Security Copilot is designed to protect, Microsoft has also committed to never use its customers data to train future Copilot iterations. Users will also be able to dictate their privacy settings and decide how much of their data (or the insights gleaned from it) will be shared. The company has not revealed if, or when, such security features will become available for individual users as well.

In yet another embarrassing development for new Twitter boss Elon Musk, court filings published Friday reveal that portions of the social media site's source code — the base programming that makes Twitter possible — have been leaked online, the New York Times reports.

Per court filings, Twitter claimed copyright infringement in an effort to have the offending code taken down from the Github collaborative programming network, where it had been posted. While the code was removed the same day, details as to how long the code had been left up were not made available, nor were the leak's scope or depth. As part of the takedown request reminiscent of Raytheon's famous -- failed -- attempt at court-sanctioned doxxing, Twitter also asked the US District Court for the Northern District of California to order Github to reveal both the identity of the user who posted the code and those who accessed and downloaded it. 

The NYT reports that, per sources within the company privy to the internal investigation into the leak, Twitter executives strongly suspect it's the work of a disgruntled employee who had left, "within the last year." Coincidentally, Elon Musk purchased Twitter last October for the eye-watering price of $44 billion and proceeded to lay-off and otherwise lose 80 percent of the company's staff, not the 75 percent that everybody feared Musk would enact in the run-up to his purchase.  

The executive who spoke with the NYT are primarily concerned that revelations gleaned from the stolen code could empower future hacking efforts, either by revealing new exploits or allowing bad actors to access Twitter user data. If the increasingly temperamental page functionality wasn't enough to send the site's user base running for the hills that the site's resurgence of scammers and white nationalists since Elon's takeover didn't already scare off, will the threat of outright hacking be the final straw for advertisers and users alike? 

The internet has connected nearly everybody on the planet to a global network of information and influence, enabling humanity's best and brightest minds unparalleled collaborative capabilities. At least that was the idea, more often than not these days, it serves as a popular medium for scamming your more terminally-online relatives out of large sums of money. Just ask Brett Johnson, a reformed scam artist who at his rube-bilking pinnacle, was good at separating fools from their cash that he founded an entire online learning forum to train a new generation of digital scam artist.

Johnson's cautionary tale in one of many in the new book, Fool Me Once: Scams, Stories, and Secrets from the Trillion-Dollar Fraud Industry, from Harvard Business Review Press. In it, Professor of Forensic Accounting at DePaul University, Dr. Kelly Richmond Pope, chronicles some of the 20th and 21st century's most heinous financial misdeeds — from Bernie Madoff's pyramid schemes to Enron and VW, and all the Nigerian Princes in between — exploring how the grifts worked and why they often left their marks none the wiser.

Harvard Business Review Press

Reprinted by permission of Harvard Business Review Press. Excerpted from Fool Me Once: Scams, Stories, and Secrets from the Trillion-Dollar Fraud Industry by Kelly Richmond Pope. Copyright 2023 Kelly Richmond Pope. All rights reserved.

Cyber Monday

I was doing my morning reading before class, and a story about a reformed cybercriminal caught my attention. I always wanted to learn more about cybercrime, but I’d never interacted with a convicted cyber offender. Here was my chance.

I did a quick Google search and found his personal website. I reached out, explained my interest in his story, and waited. By evening, I had an email from gollum@anglerphish.com. I was immediately suspicious, but it was a legit address of Brett Johnson, the man from the article.

After a few email exchanges, we got on a call. He was super friendly and had the voice of a radio DJ. I invited him to come speak to my class at DePaul.

“I teach on Monday nights for the next eight weeks, so whatever works for you will work for me,” I said.

“How about I hop in my car and come visit your class this coming Monday?” he said.

I was a little shocked—Birmingham, Alabama was a long drive— but I immediately took him up on his offer.

Brett was born and raised in Hazard, Kentucky, “one of these areas like the Florida Panhandle and parts of Louisiana, where if you’re not fortunate enough to have a job, you may be involved in some sort of scam, hustle, fraud, whatever you want to call it,” he said.

Maybe there was something in the water because his entire family engaged in fraud. Insurance fraud, document forgery, drug trafficking, mining illegal coal. You name it, Brett’s family did it.

Young Brett was a natural liar. As he grew up, he participated in the family scams.

Eventually, he branched out on his own. His first scam: in 1994, he faked his own car accident. Second scam: eBay fraud.

He reached his peak in the mid-’90s, during the Beanie Baby heyday. The Royal Blue Peanut, essentially a cobalt stuffed elephant toy, sold for as much as $1,700. Only five hundred of the dolls were manufactured, making it one of the most valuable Beanie Babies.

Brett was trying to earn some extra money. A Beanie Baby scam seemed easy and quick.

He advertised on eBay that he was selling Royal Blue Peanut for $1,500. Except he was actually selling a gray Beanie Baby that he dipped in blue dye to look like Royal Blue Peanut for $1,500.

He accepted a bid and instructed the winner to send a US postal money order. “It protects us both,” he said via email. “As soon as I get that and it clears, I’ll send you your elephant.”

The bidder sent Brett the money order; Brett cashed it and sent her his version of the blue Beanie Baby. The phone rang almost immediately.

“This is not what I ordered!” yelled a voice on the other line.

Brett’s response was swift. “Lady, you ordered a blue elephant. I sent you a blue-ish elephant.”

Brett gave her the runaround for a few weeks until she finally disappeared.

This experience taught Brett two very important lessons about cybercrime:

• Delay the victim as long as possible.

• Victims rarely report the crime and eventually go away.

Brett continued to perfect his skills and graduated to selling pirated software. From pirated software, he moved to install mod chips (a small electronic device used to disable artificial restrictions of computers or entertainment devices) into gaming systems so owners could play the pirated games. Then he began installing mod chips in the cable boxes that would turn on all the pay-per-view on clients’ TV channels for free. Then it was programming satellite DSS cards (the satellite DSS card allows access to tv channels).

He was getting requests for his cable boxes from customers all over the United States and Canada. He was on a roll. Finally, it occurred to him: Why even fulfill the cable box order? Just take the money and run. He knew that no customer would complain about losing money in an illegal transaction. He stole even more money with this updated version of his cable box scam but soon worried that he’d get flagged for money laundering. He decided he needed a fake driver’s license so he could open up a bank account and launder the money through cash taken out of the ATM.

He found a person online who sold fake licenses. He sent a picture, $200, and waited. He waited and waited. Then reality punched him in the face: He’d been scammed. The nerve.

No one hates being deceived more than someone who deceives for a living. Brett was so frustrated he started ShadowCrew.com, an online forum where people could learn the ins and outs of cybercrime. Forbes called it “a one-stop marketplace for identity theft.” The ShadowCrew operated from August 2002 through November 2004, attracting as many as four thousand criminals or aspiring criminals. It’s considered the forerunner of today’s cybercrime forums and marketplaces; Brett is known as the Godfather of Cybercrime.

“Before ShadowCrew, the only avenue you had to commit online crime was a rolling chat board,” he told my students. “It’s called a IRC chat session and stands for Internet Relay Chat.” The problem with these rolling chat screens was that you had no idea if you were talking to a cop or a crook. Either was possible.

ShadowCrew gave criminals a trust mechanism. It was a large communication channel where people in different time zones could reference conversations. “By looking at someone’s screen name, you could tell if you could trust that person, if you could network with that person, or if you could learn from that person,” he said. The screen name on the dark web became the criminal’s brand name. They keep this brand name throughout their entire criminal tenure and it helps establish trust with others, so the screen name matters.

When Brett was in class, he showed my students how information ended up on the dark web. “You can find social security numbers, home addresses, driver’s license numbers, credit card numbers on the dark web for $3,” he explained. All the information is there, practically begging to be taken.

In 2004, authorities arrested twenty-eight men in six countries, claiming they had swapped 1.7 million stolen card numbers and caused $4.3 million in losses. But Brett escaped. He was placed on the Secret Service’s Most Wanted list. After four months on the run, he was arrested.

Brett has been in and out of prison five times and spent 7.5 years in federal prison. Today he considers himself a reformed white-collar offender.

OpenAI was forced to take its wildly-popular ChatGPT bot offline for emergency maintenance on Tuesday after a user was able to exploit a bug in the system to recall the titles from other users' chat histories. On Friday the company announced its initial findings from the incident.

In Tuesday's incident, users posted screenshots on Reddit that their ChatGPT sidebars featured previous chat histories from other users. Only the title of the conversation, not the text itself, were visible. OpenAI, in response, took the bot offline for nearly 10 hours to investigate. The results of that investigation revealed a deeper security issue: the chat history bug may have also potentially revealed personal data from 1.2 percent of ChatGPT Plus subscribers (a $20/month enhanced access package). 

"In the hours before we took ChatGPT offline on Monday, it was possible for some users to see another active user’s first and last name, email address, payment address, the last four digits (only) of a credit card number, and credit card expiration date. Full credit card numbers were not exposed at any time," the OpenAI team wrote Friday. The issue has since been patched for the faulty library which OpenAI identified as the Redis client open-source library, redis-py.

The company has downplayed the likelihood of such a breach occurring, arguing that either of the following criteria would have to be met to place a user at risk:

- Open a subscription confirmation email sent on Monday, March 20, between 1 a.m. and 10 a.m. Pacific time. Due to the bug, some subscription confirmation emails generated during that window were sent to the wrong users. These emails contained the last four digits of another user’s credit card number, but full credit card numbers did not appear. It’s possible that a small number of subscription confirmation emails might have been incorrectly addressed prior to March 20, although we have not confirmed any instances of this.

- In ChatGPT, click on “My account,” then “Manage my subscription” between 1 a.m. and 10 a.m. Pacific time on Monday, March 20. During this window, another active ChatGPT Plus user’s first and last name, email address, payment address, the last four digits (only) of a credit card number, and credit card expiration date might have been visible. It’s possible that this also could have occurred prior to March 20, although we have not confirmed any instances of this. 

The company has taken additional steps to prevent this from happening again in the future including adding redundant checks to library calls, "programatically examined our logs to make sure that all messages are only available to the correct user," and "improved logging to identify when this is happening and fully confirm it has stopped." The company says that it has also reached out to alert affected users of the issue.

This news follows a costly public faux pas committed by Google's rival Bard AI in February when it incorrectly assured Twitter that the JWST was the first telescope to image an exoplanet, as well as revelations that CNET had surreptitiously used generative AI to write financial explainer posts (a week before laying off a sizable chunk of its editorial department). Whether OpenAI will suffer the same market-based repercussions as its competitors remains to be seen.