The Curious Case of AI’s Future in Formula 1
What happens when paddock politics flirt with artificial intelligence?
Formula 1 brings a host of influencers and A-list celebrities parading around the paddock each race weekend. But among Hollywood’s high society, two faces stood out at the Miami Grand Prix last May. Tesla’s Elon Musk and Amazon executive Jeff Bezos mirrored the tech tycoon sponsors plastered on drivers’ crash helmets, teams’ cars and tracks’ hospitality lounges.
Those software mogul dollars reach further than the track and trickle into the sport’s most vital asset: data.
F1 is a tech-heavy sport; it always has been. The racing series has evolved from the string and duct tape airflow indicators of the olden days to 300-plus sensors streaming 10,000 measurements per second and roughly 11.8 billion data points per season into an eye-glazing data dump, according to F1’s technical analysts.
It has always been a numbers game with a series of questions best answered by algorithms: Where are the car’s weak points? Where is the team losing speed? When is the best time to pit for new tires? What is the best maneuver around turn five?
Temperature, weight, height, distance, speed, humidity, fuel load, aerodynamic downforce and, the most vital factor, time are just a handful of numbers that flash across a data analyst’s screen while the car is on track.
For a sport heavily reliant on untangling equations and contextualizing decimals, these analysts are far and few between, according to McLaren’s team analyst Jessica Tomkins. Parts specialists are now responsible for compiling and analyzing large data sets without always having the skills or education of a statistician. It’s no wonder, then, that artificial intelligence (AI) helps filter through the noise for a growing population of, what the tech industry calls, citizen data analysts.
A brief glance around the garages gives a good idea of just how prolific AI is in the series. Mercedes partners with TIBCO. McLaren has Dell Technologies and Alteryx. Red Bull leans on IBM and its title sponsor, Oracle, while Ferrari teams up with Amazon.
Improved car performance, advanced safety features, lengthened tire stints and strategized pit stops all count on AI to better inform split-second decisions. The technical brain behind data analysis systems can keep up with the blizzard of numerals and pick out valuable insights from the storm of information.
As simulated racing technology grows — once just a way for drivers to test tracks and now a recognized e-sport category — teams can save money and time by testing new parts and strategies without risking driver safety in the process. F1, in its ceaseless mission to attract a bigger fan base, also uses AI to create tighter, more cutthroat racing made for TV.
Despite its merits in the world of racing, AI has a bad rap.
College students are breezing by advanced history classes with auto-generated essays and robots are taking over warehouse and factory jobs. There is an unsettling feeling that follows reading news articles, browsing captions and admiring art when the words or creators behind them are manufactured and the investment in research is hollow.
This wave of tech isn’t likely to slow down. Europol estimates by 2026, roughly 90% of digital content could be AI-generated. From social surveillance tendencies to phone scams to art forgery, the Big Brother effect paints an ill-fated future.
Even the well-intentioned use of AI doesn’t sit well for some. “[I am] absolutely terrified about the future of art and humanity but this is pretty,” a user commented on an AI-generated Lana Del Ray cover.
When AI seeps into the humanities and the political realm, things begin to look ugly.
F1 is currently testing that boundary.
In 2022, the sport’s ruling body, the Federation Internationale de I’Automobile (FIA), partnered with Arwen.ai, an artificial intelligence company, to reduce cyber abuse in online F1 communities. The FIA said the system cut discriminatory and problematic social media comments on Mercedes’ accounts by 70%.
The success story and calls from drivers to extend AI’s reach within the sporting authority means automated tech may pop up past the pit lane.
At the Singapore Grand Prix earlier this fall, AI’s presence as a penalty predictor was recommended after the FIA failed to penalize Red Bull’s Max Verstappen for impeding another driver during qualifying. Mercedes driver Lewis Hamilton made headlines for suggesting the ruling body “start looking into AI for this sort of thing, so we get good decisions.”
Penalty debates in Formula 1 are nothing new. Whether drivers should or should not be punished is a common discussion plaguing the paddock and social media platforms. While AI already helps teams advance safety and has built some of the fastest sports cars known to man, its entry into the F1 courthouse poses both possibilities and problems for the future of F1.
The debate around track limits, for example, came to a head this season in Austria when up to 1,200 track limit violations were flagged during the race. The problem continued in Qatar where 51 lap times were deleted when all four tires breached the white track lines.
Ahead of the U.S. Grand Prix in Austin, the FIA expanded the track for wider margins at particularly tricky turns. However, extending a few inches of road didn’t solve the issue of drivers challenging stewarding decisions, leaving some fans to suggest AI give a helping hand.
A driver, player or competitor will always challenge the ref, especially when millimeters are thrown into question. F1 is far from the only sport to test AI to prevent such arguments from breaking out. The English Premier League is relying on AI to help determine whether the ball fully crosses the goal line and basketball is using synthetic computer systems to cut through flawed officiating.
But referees are in danger of becoming a dying breed.
In September, The Independent reported that in 30 years AI could replace umpires and referees. After all, it’s more difficult to point the finger of blame at a software program you can’t quite comprehend — even if it has its own biases.
Could motorsport stewards face the same fate?
While AI may help monitor small margins that could cost drivers the race, things get precarious when aiding turns into replacing. AI data collection and analysis may seem straightforward, but its use in the motorsport policing process risks becoming a slippery slope.