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Will AI violate human rights? Humanitarian groups are trying to make sure they don’t
A group of human rights organizations has signed the Toronto Declaration on Machine Learning, an initiative that calls for regulations designed to protect people from human rights violations caused by artificial intelligence. The declaration was signed on Wednesday, with groups such as Amnesty International, Access Now, Human Rights Watch, and the Wikimedia Foundation pledging their support.
The Toronto Declaration is rather unique in the way that it draws from international human rights laws. According to the declaration, it is imperative for people who are discriminated against by AI-based systems to have an avenue where they can seek reparations, considering that intelligent machines would likely “learn” implicit biases based on the information that they are fed. As could be seen in the declaration’s Preamble, the emergence of new technologies lies the need to develop new ways to protect human rights, particularly among diverse individuals and marginalized groups. The declaration further noted that AI-based technologies could “exacerbate discrimination at scale.”
“Existing patterns of structural discrimination may be reproduced and aggravated in situations that are particular to these technologies – for example, machine learning system goals that create self-fulfilling markers of success and reinforce patterns of inequality, or issues arising from using non-representative or “biased” datasets.
“All actors, public and private, must prevent and mitigate discrimination risks in the design, development and, application of machine learning technologies and that ensure that effective remedies are in place before deployment and throughout the lifecycle of these systems.”
Apart from the rights to equality and non-discrimination, the Toronto Declaration also highlights the importance of developing safeguards against possible AI-driven human rights violations in areas such as privacy, data protection, freedom of expression, participation in cultural life, equality before the law, and meaningful access to remedy. The declaration also notes that intelligent computer systems that make decisions and process data can implicate economic, social, and cultural rights, such as the provision of healthcare and education, as well as access to labor and employment.
In order to prevent human rights violations caused by artificial intelligence, the Toronto Declaration has called on developers to foster inclusion, diversity, and equity to ensure that AI-based systems do not develop discriminatory behavior.
“Intentional and inadvertent discriminatory inputs throughout the design, development and, use of machine learning systems create serious risks for human rights; systems are for the most part developed, applied and reviewed by actors which are largely based in particular countries and regions, with limited input from diverse groups in terms of race, culture, gender, and socio-economic backgrounds. This can produce discriminatory results.
“Inclusion, diversity, and equity entails the active participation of, and meaningful consultation with, a diverse community to ensure that machine learning systems are designed and used in ways that respect non-discrimination, equality, and other human rights.”
The full text of the Toronto Declaration on Machine Learning can be accessed here.
The inherent risks of hyper-intelligent machines are one of the key reasons behind the creation of OpenAI; a nonprofit organization co-founded by Elon Musk aimed at developing artificial intelligence that is inherently safe for people. While Musk has since stepped down from his post as a board member of OpenAI, the organization has shown signs that it is in the process of expanding. Earlier this year, for one, OpenAI announced that it is actively hiring a Recruiting Coordinator, who will be tasked to help grow the company’s team.
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Tesla makes good on its Cybercab promise in just two weeks
Tesla Cybercab riders can now pull up a rear camera view and darken the screen.
Tesla has given Cybercab passengers a way to see what is behind them, along with a way to turn the cabin screen off entirely.
Riders in Austin can now bring up a live rearview camera feed on the Cybercab’s center display in the middle of a trip. Austin rider Ethan McKanna spotted the change late Friday night, posting from a ride that “You can now open the camera to view what’s behind you in Cybercab!” His photo shows a strip of rear camera video across the top of the screen, with another Cybercab following on a bridge. Sawyer Merritt shared the image Saturday and wrote that it “sounds like” there is also a new quiet mode that darkens the entire screen for riders who want to relax, sleep, or avoid a bright display at night.
The camera view goes beyond the rear feed. Tesla UI software engineer Evan, who posts as @CarCoder, replied to McKanna with a tip: “You can also tap it to see more cameras, and swipe it up or down to hide and show.” Until now, the Cybercab only showed its rear and repeater feeds on the “Please Exit Safely” screen at the end of a ride, so passengers could check for cyclists and traffic before opening a door.
Quiet mode surfaced a day earlier. Austin rider Jackson Blatz posted a video Friday morning of the new Robotaxi interface in a Cybercab with the option. Tesla has not published release notes for either feature.
The rear camera view moved quickly from request to release. Earlier this month, Cybercab rider Dan Burkland asked Tesla to let passengers pull up the rear and repeater cameras whenever they want, “especially for peace of mind.” Evan answered “In development,” as Teslarati reported at the time. About two weeks later, riders have it.
The feature fills a gap created by the Cybercab’s design. With no steering wheel, no pedals, no mirrors and no rear window, a passenger has no natural way to glance behind the car. The eight exterior cameras that feed Tesla’s autonomy software were already on board, so the change only required software.
There is also an AI angle to how it was built. Yun-Ta Tsai, a senior staff engineer on Tesla’s AI team, quoted Merritt’s post and wrote that the “(human) camera view tuning is optimized with Grok and implements part of the algorithm by directly programming the fixed-function hardware, so I don’t even need to check the datasheet.” Tsai did not say which part of the algorithm Grok handled. Grok already plays a bigger role inside the vehicle, with Grok Bot now enabled across every Cybercab and the Model Y Robotaxi fleet after Tesla brought the agent into its cars in September.
The two features join a busy week of changes for riders in Austin, which also brought a redesigned Live Activity for iPhone and Apple Watch and live trip sharing. They also arrive as Tesla prepares the Cybercab for life outside its own fleet. On the third quarter earnings call, Lars Moravy said the company is aiming to deliver Cybercabs to customers before the end of 2026. Tesla has not said whether the camera view and quiet mode will also come to its Model Y Robotaxis.
Elon Musk
Tesla shows what Roadster drivers will see on screen before thruster activation
Tesla’s Roadster video reveals a fighter jet inspired cockpit with a 5,500 PSI thruster gauge.
Tesla has given future owners their clearest look yet at the cockpit of its next generation Roadster. In a 34 second video posted to X on Friday afternoon, the company walked through the car’s touchscreen with a caption: “Inspired by fighter jet cockpits, Roadster’s interface was designed around the pilot.”
The clip opens on a black screen with red graphics and a 3D wireframe of the car, which sits beside the Roadster’s squared off yoke. Tapping parts of the model brings up controls for the rear wing, including low drag and high downforce positions, along with a charging page with a charge limit bar and a small music player. A row of tabs along the bottom reads Home, Vehicle, Listen, Climate and Navigate.
Most of the video is spent in Track Mode. The dashboard shows a live circuit map, a list of session lap times, brake and motor temperatures, and pressure and temperature readouts for each tire. A setup page lets the driver pick Auto, Low Drag, High Downforce or Custom aero modes, adjust aero balance and brake balance, and switch stability and traction control off. Along the bottom, a status bar reads “Thruster · 5,500 PSI” next to a “Boost Ready” indicator.
That gauge ties the software to the hardware Tesla showed off near Waco, Texas on October 15. The Thrust and Rocket versions use cold gas thrusters fed by carbon overwrapped pressure vessels, and Tesla lists 0 to 60 mph times of under 0.9 seconds and under 0.59 seconds for them, as Teslarati detailed in its breakdown of the three Roadster configurations. The base Performance car relies on a fan and ground sealing system for grip, and the aero settings on screen match the active wings and suction setup covered in our look at how the Roadster generates downforce.
The Roadster layout is a departure from the rest of Tesla’s lineup. Instead of a map centered screen, the Roadster puts the car itself at the center of the home page, and Tesla’s Roadster page lists two smaller forward displays alongside the main touchscreen. Tesla has not said whether any of the Track Mode telemetry will make its way to the Model 3 Performance or other vehicles.
The interface could still change before deliveries. Elon Musk said at the event that Roadster production will begin in 2028, and Tesla says the flagship Rocket version is not approved for public road use. Reservations are open with a $50,000 payment, while Thrust is listed as a limited release and Rocket is invite only.
Those who want to see the car in person will get their first chance this weekend. The Roadster goes on display in the lobby of the Petersen Automotive Museum in Los Angeles from October 24 to 27, according to Sawyer Merritt, the first time the public will be able to view it up close.
Elon Musk
Tesla reveals Optimus Academy, where robots teach themselves
Tesla has begun building production quality Optimus robots in Fremont and revealed its training plan.
Tesla has started building Optimus on the high volume line it set up inside its Fremont factory, and the company says the robots coming off it are the first that meet the bar for a real product. “The bots coming off this line are the first production-quality bots that we have manufactured,” Tesla wrote in its third quarter shareholder letter, adding that it has “proven that the current manufacturing process for Optimus is suitable for a commercial product.”
The line sits in space that built the Model S and Model X until this spring. Tesla cleared the old vehicle line in 46 days, as Teslarati reported in July, to make room for robot production sized for one million units a year. On Wednesday’s earnings call, Elon Musk said most of the equipment for that capacity is already in Fremont, with output set to climb toward roughly 20,000 robots a week as the line ramps.
Musk described the ramp as a classic S curve. “The growth of Optimus is an S curve, but the initial curve is a shallow slope,” he said. The team is now refining the robot’s AI, electromechanical design, reliability and service life, and Musk expects that work to be finished by the end of next year, when Tesla plans to start delivering Optimus to outside companies for dangerous, repetitive and around the clock jobs.
The most interesting part of the call was how Tesla plans to teach the robots. Its cars send real driving data back to the AI team from millions of vehicles, but Optimus has no fleet like that yet. “A big difference with Optimus versus the cars is we don’t have this vast fleet of cars from which we can gather training data,” Musk said. Tesla’s answer is an Optimus Academy, where 10,000 to 20,000 robots will practice a wide range of tasks and feed what they learn into the next version of the model. Every unit off the Fremont line becomes a source of that training data.
Smarter hardware is on the way too. Tesla plans to put its AI5 chip into Optimus next year, and Musk said a new Optimus video should arrive within one or two months showing the robot completing tasks driven by AI rather than preprogrammed motions. He took aim at rival humanoid demos that only run scripted routines, saying those would not hold up in the real world.
The supply chain is lining up behind the program. In September, Tesla certified Tuopu, Joyson and Sanhua as mass production partners for Optimus components. A far larger Optimus factory is also rising at Giga Texas, where drone footage from Joe Tegtmeyer showed the steel frame nearing completion, and Musk has pegged that plant’s long term target at 10 million robots a year.
Tesla executives also said Optimus production costs are trending toward the expected manufacturing cost of Cybercab, a sign the robot is being engineered for volume from the start. The hands remain the toughest piece of the design, a point Musk also made at the X Takeover event earlier this month, as Teslarati covered at the time, and that is where much of the current engineering effort is focused.