Having a real conversation with a computer is fun and uncomfortable. Thanks to the rapid development of generative artificial intelligence, many of us are now exposed to this revolutionary technology, which has huge implications for how people live, work and communicate around the world. The full extent of the potential of generative AI is still up for debate, but there is no doubt that it will be very disruptive.
The last time we experienced such widespread social change fueled by technology was the Web 2.0 era of the mid-2000s. New, emerging companies like Facebook and Google revolutionized communications and delivered popular services to a rapidly growing user base.
But those innovative services have come at a price. Initially conceived as free services Generated by widely monitored revenue People and businesses that use them. The result is an online economy that relies on the collection and sale of our personal information to access increasingly important services.
These business models pushed companies to grow endlessly Invasive ways to track usAnd the Federal Trade Commission will eventually find reason to believe that Several of These Companies He had. He broke the law. Combined with aggressive tactics to buy or lock out companies that threaten their position, these tactics have strengthened the dominance of a few companies. What started out as a revolutionary set of technologies has ended up with large private power focusing on key services and locking down business models that come at a staggering cost to our privacy and security.
The journey to the Web 2.0 era was not inevitable—rather, it was shaped by a number of policy choices. And now we face another election period. As the use of AI becomes more widespread, government officials have a responsibility to ensure that this hard-learned history does not repeat itself.
As companies race to deploy and monetize AI, the Federal Trade Commission is taking a closer look at how we can best achieve our combined responsibilities to promote fair competition and protect Americans from unfair or deceptive practices. As these technologies evolve, we are committed to doing our part to preserve America’s long-standing tradition of maintaining open, fair, and competitive markets that have underpinned both innovation and our nation’s economic success — regardless of business models or the mass exploitation of their consumers. Although these tools are novel, they are not exempt from existing laws, and the FTC will vigorously enforce the laws we govern even in this new market.
Although the technology is moving fast, we can see many risks. Widening adoption of AI threatens to further entrench the market dominance of big tech companies. A handful of powerful businesses dominate. Important raw materials Where startups and other companies rely to develop and deploy AI tools. This includes cloud services and computing power, as well as vast data stores.
Enforcers and regulators must be vigilant. Dominant firms can use their control over these key resources to pick winners and losers in ways that further enhance their dominance. Meanwhile, AI tools are being used by organizations to determine everything from laundry to pricing Bowling lane reservations It can facilitate collusive behavior that unfairly raises prices – as well as well-targeted price discrimination. Regulators have a dual responsibility to monitor the risks posed by new AI technologies while promoting fair competition to ensure that markets for these technologies develop legally. It’s the FTC. Well equipped with legal authority To address the issues raised by the rapidly growing AI sector, including collusion, monopolization, mergers, price discrimination and unfair competition practices.
and generative AI risks turbocharging fraud. It may not be ready to replace professional writers, but it does a much better job of crafting a message that feels more authentic than your average artist — enabling scammers to generate content faster and cheaper. Chatbots are being used to lure people, fake websites, and generate spear phishing emails designed to scam people. Fake consumer reviews -Bots are instructed to use words or phrases targeted at specific groups and communities. Fraudsters eg Can prepare highly targeted phishing emails. Based on individual users’ social media posts. Alongside tools that create deeply fake videos and audio clones, these technologies can be used to greatly facilitate fraud and spoofing.
When we enforce the law’s ban on deceptive practices, we look not only at the fly-by-night fraudsters who deploy these tools, but also at the upstream organizations that enable them.
Finally, these AI tools are being trained on large databases in largely unsupervised ways. These technologies pose a risk because they can be fed information full of errors and biases Automate discrimination – Locking people out of jobs, housing or key services. These tools can be trained on private emails, chats and confidential information, ultimately exposing personal details and violating user privacy. Without Laws Non-discrimination will apply, and existing authorities will prohibit exploitative collection or use of personal information.
The story of the growth of tech companies two decades ago serves as a warning about how we should think about the spread of generative AI, but history also has lessons for how to handle technological disruption for the benefit of all. Facing antitrust scrutiny in the late 1960s, computing titan IBM phased out software from its hardware systems, spurring the growth of the US software industry and generating trillions of dollars in growth. The government action required AT&T to open its patent and disclose the same. Decades of innovation And it inspired the growth of countless young organizations.
America’s longstanding national commitment to foster fair and open competition is an important part of what has made this nation an economic powerhouse and innovation laboratory. Again we find ourselves at a key decision point. Can we continue to be the world’s leading technology house without embracing bottom-up business models and monopolistic control that shuts down high-quality products or the next big idea? Yes – if we make the right policy choices.
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