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When the U.S. government signs contracts with private technology companies, the fine print rarely reaches the public. Palantir Technologies, however, has attracted more and more attention over the past decade because of the size and scope of its contracts with the government. Palantirs two main platforms are Foundry and Gotham. Each does different things. Foundry is used by corporations in the private sector to help with global operations. Gotham is marketed as an operating system for global decision making and is primarily used by governments. I am a researcher who studies the intersection of data governance, digital technologies, and the U.S. federal government. Im observing how the government is increasingly pulling together data from various sources, and the political and social consequences of combining those data sources. Palantirs work with the federal government using the Gotham platform is amplifying this process. Gotham is an investigative platform built for police, national security agencies, public health departments, and other state clients. Its purpose is deceptively simple: take whatever data an agency already has, break it down into its smallest components, and then connect the dots. Gotham is not simply a database. It takes fragmented data, scattered across various agencies and stored in different formats, and transforms it into a unified, searchable web. The stakes are high with Palantirs Gotham platform. The software enables law enforcement and government analysts to connect vast, disparate datasets, build intelligence profiles, and search for individuals based on characteristics as granular as a tattoo or an immigration status. It transforms historically static recordsthink department of motor vehicles files, police reports, and subpoenaed social media data like location history and private messagesinto a fluid web of intelligence and surveillance. These departments and agencies use Palantirs platform to assemble detailed profiles of individuals, mapping their social networks, tracking their movements, identifying their physical characteristics, and reviewing their criminal history. This can involve mapping a suspected gang members network using arrest logs and license plate reader data, or flagging individuals in a specific region with a particular immigration status. The efficiency the platform enables is undeniable. For investigators, what once required weeks of cross-checking siloed systems can now be done in hours or less. But by scaling up the governments investigative capacity, Gotham also alters the relationship between the state and the people it governs. Shifting the balance of power The political ramifications of Palantirs rise come into focus when you consider its influence and reach across the government. U.S. Immigration and Customs Enforcement alone has spent more than $200 million on Palantir contracts, relying on the software to run its Investigative Case Management system and to integrate travel histories, visa records, biometric data, and social media data. The Department of Defense has awarded Palantir billion-dollar contracts to support battlefield intelligence and AI-driven analysis. Even domestic agencies like the Centers for Disease Control and Prevention and the Internal Revenue Service, and local police agencies like the New York Police Department, have contracted with Palantir for data integration projects. These integrations mean that Palantir is not just a vendor of software; it is becoming a partner in how the federal government organizes and acts on information. That creates a kind of dependency. The same private company helps define how investigations are conducted, how targets are prioritized, how algorithms work, and how decisions are justified. Because Gotham is proprietary, the public, and even elected officials, cannot see how its algorithms weigh certain data points or why they highlight certain connections. Yet the conclusions it generates can have life-altering consequences: inclusion on a deportation list or identification as a security risk. The opacity makes democratic oversight difficult, and the systems broad scope and wide deployment means that mistakes or biases can scale up rapidly to affect many people. Beyond law enforcement Supporters of Palantirs work argue that it modernizes outdated government IT systems, bringing them closer to the kind of integrated analytics that are routine in the private sector. However, the political and social stakes are different in public governance. Centralized, attribute-based searching, whether by location, immigration status, tattoos or affiliations, creates the capacity for mass profiling. In the wrong hands, or even in well-intentioned hands under shifting political conditions, this kind of system could normalize surveillance of entire communities. And the criteria that trigger scrutiny today could be expanded tomorrow. U.S. history provides warning examples: The mass surveillance of Muslim communities after 9/11, the targeting of civil rights activists in the 1960s, and the monitoring of anti-war protesters during the Vietnam era are just a few. Gothams capabilities may enable government agencies to carry out similar operations on a much larger scale and at a faster pace. And once some form of data integration infrastructure exists, its uses tend to expand, often into areas far from its original mandate. A broader shift in governance The deeper story here isnt just that the government is collecting more data. Its that the structure of governance is changing into a model where decision-making is increasingly influenced by what integrated data platforms reveal. In a pre-Gotham era, putting someone under suspicion of wrongdoing might have required specific evidence linked to an event or witness account. In a Gotham-enabled system, suspicion can stem from patterns in the datapatterns whose importance is defined by proprietary algorithms. This level of data integration means that government officials can use potential future risks to justify present action. The predictive turn in governance aligns with a broader shift toward what some scholars call preemptive security. It is a logic that can erode traditional legal safeguards that require proof before punishment. The stakes for democracy The partnership between Palantir and the federal government raises fundamental questions about accountability in a data-driven state. Who decides how these tools are used? Who can challenge a decision that was made by software, especially if that software is proprietary? Without clear rules and independent oversight, there is a risk that Palantirs technology becomes normalized as a default mode of governance. They could be used not only to track suspected criminals or terrorists but also to manage migration flows, monitor and suppress protests, and enforce public health measures. The concern is not that these data integration capabilities exist, but that government agencies could use them in ways that undermine civil liberties without public consent. Once put in use, such systems are hard to dismantle. They create new expectations for speed and efficiency in law enforcement, making it politically costly to revert to slower, more manual processes. That inertia can lock in not only the technology but also the expanded scope of surveillance it enables. Choosing the future As Palantir deepens its government partnerships, the issues its technology raises go beyond questions of cost or efficiency. There are civil liberties implications and the potential for abuse. Will strong legal safeguards and transparent oversight constrain these tools for integrated data analysis? The answer is likely to depend on political will as much as technical design. Ultimately, Palantirs Gotham is more than just software. It represents how modern governance might function: through data, connections, continuous monitoring, and control. The decisions made about its use today are likely to shape the balance between security and freedom for decades to come. Nicole M. Bennett is a PhD candidate in geography and assistant director at the Center for Refugee Studies at Indiana University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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E-Commerce
While another person might worry about AI cannibalizing their industry, will.i.am sees enormous potential in AI to change everything: from how we create music to the way we work. will.i.am is a founding member of the Black Eyed Peas. Hes racked up nine Grammy Awards and written over 130 songs. Hes also the founder of FYI.AI, an AI-powered productivity app for creatives that allows them to message each other, video call, and chat with an AI to generate ideas. In this interview, premium subscribers will learn: The true purpose of AI for creatives (it’s not saving time) How to ground everything you do in supporting your community Why will.i.am balances his optimism with a desire for technological guardrails I catch will.i.am on a layover in London. Hes just wrapped up a concert with Shakira, en route to Saudi Arabia for what he calls Black Eyed Peas business. The week before, he was in India working on his partnership with chipmaker Qualcomm. I ask him how he manages to get enough sleep, and he looks me dead in the eye and says: On the plane. As if thats truly enough rest to power creative genius. On top of being an AI founder and world famous musician, will.i.am runs a foundation that provides educational opportunities to underserved youth. Hes also a tech investor with an uncanny ability to spot the next big thing: Hes made early investments in Open AI, Pinterest, Dropbox, and Anthropic. Most recently, in March, he launched that partnership with Qualcomm, where FYI.AI will be on its Snapdragon line of chips, which powers phones, PCs, and cars. As we talk, he circles through the airport, laying out his greatest fears and deepest hopes for AI. The sun is setting over London ushering in a new day, and will.i.am is rapping and rhyming, filled with an exuberance thats catching. He has an unwavering faith that despite the threat of AI stealing jobs and fears around misuse and lack of regulation, humanity will manage to use AI for the greater good, somehow finding the love. [Photo: Getty Images] Fast Company: How do you figure out what the next big thing for yourself is? Well, first, lets start with the word biglets refrain from using it. Sometimes, the thing youre chasing isnt big. Sometimes theyre just things you love. Sometimes they are pieces that help complete your puzzle. I don’t do things that don’t align with the main objective. Whats the main objective? I come from the inner city, and the inner city has low investment in education. Folks that look like meBlack and brown folksare on a school-to-prison pipeline. Sometimes cradle-to prison-pipeline. Most of my friends that I grew up with are either dead or in prison. The objective is to go back to my community, to ensure that there’s a different path. So I started [education nonprofit i.am. Angel Foundation] with just 65 kids. Now it serves about 15,000 students. If it doesn’t [show] folks that come from communities that resemble the conditions I come from what’s possible, then I won’t do it. I don’t like doing things just for checks. I don’t do things that don’t align with the main objective. Sometimes it’s a small thing, sometimes it’s a little thing that doesn’t paybut it adds. Youre a musician, investor, founder, and activist, among other roles. How do you think about career growth? Hip-hop. Hip-hop taught me to do that. Hip-hop was educational. It taught kids in my generation what they didn’t teach us in school. It taught us how to be a community. I learned music not because of school, but because of hip-hop. They didnt even have music programs in a lot of these inner cities, but hip-hop became my Calvary. I’m so happy I was raised in that era of hip-hop when its foundations were about community outreachgiving kids in the inner city a path away from violence. Now its turned into glorifying the drug dealers. As matter of fact, what got me into tech was a website called Okayplayer, which [was founded by] Questlove. [Editors note: Okayplayer was an early online musical community founded in 1999. It was one of the first places where fans could interact directly with artists.] He was a part of that website before MySpace, before Facebook, before Friendster. We all used to go on that in like 1999, 2000, 2001 and that’s how we all connected and in chat rooms. My handle was peasforyou. This was our social media. What [also] got me into technology? Well, the sampler. I play the computer. I don’t play an instrument. I played a fucking computer. All the folks that make beats as their instrument, are all hyper technological. Dr Dre is a beat maker. Arabian Prince is a beat maker. Theyre all tech-leaning. Youre the founder of an AI company. But how do you think AI will end up impacting the music community? Imagine its 1825. The record industry didnt exist then. So you listened to music in your home, or you had to have a band play it, or you go to the theatre or opera, or church. It wasnt available on the ready. Then, when the record industry came along, song form had to change, because there was a limited amount of information you could put on the lacquer. Song structure had to change. So, learning from this shift: You could use your imagination to dream up the next industry. Yes, AI is a great mimic. It could spit out a whole bunch of shit in five minutes that took us hours to do. But is that what it’s supposed to do? Just like a regurgitation of imagination, regurgitation of emotion? Or are you supposed to utilize this technology to dream some shit up that never existed? [Back in the day] do you think motherfuckers was like, yo, hip-hop music? As a matter of fact, they’re like, that aint music. How you say that’s music? You sample other people’s music. If there’s any genre that is aligned with AI’s principles, it would be hip-hop. We call them samples; AI calls them data sets. I could take this song and that song and this song and that songand make a new sog. Oh, that kind of sounds like fucking AI, doesn’t it? What if instead of this neural network, it’s a simulated neural network. It’s a fusion model. Right now is the time to dream up some new fucking shit. I’m excited all the time. I wake up every day like, let’s create. Its this energy that we could use for good. We can solve problems and identify how to be helpful to communities. We can dig deep inside and be a fucking light. Help folks in the darkness. Thats what keeps me leaping out of bed every single day. I love the hope here. But what advice do you have to people who are afraid of losing their jobs because of AI? Its a really good question. That is something to be concerned about: job replacement, job displacement, and this side of the tsunami thats coming. A lot of white-collar jobs are threatened, [as well as] blue-collar jobs. But theres other jobs that people can do that didn’t exist yesterday. Somebody had to dream that stuff up. Well, let’s start dreaming up some shit. AI doesn’t imagine. AI doesn’t dream shit up. We do that. So if reality is not shipping 100%, and there’s room for imagination and dream, fucking bring on the dreamers. Fund the big ideas. Go. Dream up some shit. Make sure that everybody can work, though. Because if you leave it to the corporations, they dont care. That’s how we got here in the first place. So we’re here because they lead with greed. I do have some boogeymen, some boogie woogies, where Im like, I dont know the answer to that. Let me stay optimistic. What boogie woogies do you have? You know, music was hijacked. Hip-hop was turned into prison commercials. The movement was taken over. Every time theres progress, theres this trip wire of regress. Right now, people live on the device. They trust the machine. They dont even know their digital life is not more valuable than their analog life. I see the concernsanyone can buy your data to manipulate you. We need some regulations so the data practices of the past are not borrowed right now. So no matter how optimistic I get, I think we need some help. We need someone thinking about how to ensure were safe. Look at the city over there, the beautiful bridge, the carsthey feel safe. I dont have to worry about standing in the middle of the road, because I know someone is going to slow down. I hope we get governance and guidance. To drive a car, I have to have a license. But in this AI space, no one, not even me, had to take a basic test to make sure you have the right principles in place to deploy products where people are safe, and your moral compass isnt leading with greed. Regulations should not stifle innovation. But lets make sure there arent whackos behind the wheel.
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E-Commerce
Companies are investing heavily in AI, in spite of the fact that they aren’t yet seeing a big return. A recent report from MIT found that 95% of organizations that have adopted AI haven’t seen any return on the investment at all. (However, the 5% of companies who are seeing the return are “extracting millions in value,” according to the report.) Despite these odds, according to a Nexford University survey of 1,000 U.S. individuals (800 recently laid off workers and 200 hiring managers), companies are increasingly viewing AI as a valuable tool and a must-have for employees. For employees, AI might just be the key to surviving layoffs, or the necessary qualification for landing the next job. According to the survey, layoffs are happening at an astonishingly high rate: 65% of companies conducted layoffs in the past 12 months. While 68% of companies identified cost-cutting as the reason for layoffs, 32% mentioned skill mismatch, and 31% and 27% cited “company strategy shift and AI adoption, respectively. In fact, almost half (49%) of employers say theyre more likely to retain the workers with strong AI skills. Likewise, when it comes to new hires, employers want workers who understand AI. About one-third (29%) of hiring managers said they are exclusively hiring employees who are proficient with AI. Workers are catching on. Nearly one in five recently laid-off workers (19%) say AI adoption contributed to them being let go, and this increases for younger workers: 23% of Gen Z workers said AI was behind their layoff, as do 21% of millennials, compared to just 14% of Gen X and baby boomers. Many laid-off workers are taking action. Since losing their jobs, two thirds are focusing on reskilling. A quarter are studying coding, while 22% are studying AI fundamentals and another 22% are studying prompt-engineering. To reskill, over half (56%) use YouTube and other online tutorials to enhance their skill set, and 39% are taking an online course. On average, respondents who are focusing on upskilling are spending an average of six hours a week on learning, with a third of that time focused on AI specific skills. However, nearly a quarter of respondents (24%) pointed out cost is a barrier to upskiling, and more than one in five (21%) say they aren’t sure what they should be learning to make themselves hirable while 17% point to time constraints. Regardless of the value AI brings to the table, its clear at the moment employers see it as a necessary skillset and workers are following their lead.
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E-Commerce
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