In the rapidly emerging artificial intelligence economy, organizations will split into two groups: those who are good at AI and those who are bad at business.
Most experts agree that AI won’t replace humans, but instead augment us in a world of mixed autonomy. You’ll need new structures to harness AI’s transformative potential while managing its very real risks—the biggest of which is data privacy.
So how can leaders handle AI and privacy risks? Prepare for AI-related data privacy regulations, develop a strategic vision for mixed autonomy that trains humans to assess AI-generated content, and adopt a private AI approach.
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1. AI regulations are coming.
If 2023 was the breakout year for AI, expect 2024 to be the year of AI regulation. Regulations have started to take shape in the United States, among other countries, as governments recognize the potential impacts AI could have on society—from user privacy concerns to misinformation to cybersecurity risks. The European Union has even been debating its own AI Act to curb potential misuse of the technology.
While most of the discussions to date have painted in broad strokes how we might start to address major concerns, business and IT leaders should expect more comprehensive privacy legislation in 2024 in the form of privacy laws from the US Congress as well AI data privacy governance frameworks from regulatory agencies.
It’s unclear how these discussions will ultimately take shape. But it’s a trend that leaders should be watching—regulations will come soon and organizations will have to adapt in kind.
2. Humans and AI should work harmoniously.
The integration of humans and AI in collaborative efforts is crucial to addressing AI data privacy challenges and ensuring responsible AI usage. Unlike the dystopian narratives that envision AI replacing humans entirely, the current reality emphasizes a more balanced approach.
“Organizations must have a strategic vision for mixed autonomy—in other words, how they will use AI to augment humans, rather than replace them.”
– Michael Beckley, CTO, Appian
AI lacks the autonomy to replace human judgment or expertise entirely—a big reason why business and IT leaders need to develop a strategic vision for mixed autonomy, leveraging AI to augment human capabilities rather than supplant them. AI left to its own devices can make incorrect predictions or perpetuate bias; humans must be kept in the loop to ensure these don’t occur and lead to disastrous consequences.
This partnership is exemplified in tasks like generating emails or correspondence, where AI can propose content, but human oversight is essential to prevent data privacy issues and ensure accuracy. For instance, in fields like healthcare, where sensitive information is involved, human intervention becomes critical to verify if AI-generated messages are devoid of hallucinated details and refrain from leaking personal data. Organizations that train individuals to assess and edit AI-generated content for compliance and ethical considerations can avoid some of the most common data privacy concerns that come with using AI for sensitive information.
3. Businesses will need private AI.
While public AI models started the recent AI craze, pressing data privacy concerns about them have quickly cut the blind infatuation short.
OpenAI briefly banned ChatGPT in Italy in early 2023 due to potential GDPR privacy violations. And companies across sectors have limited their usage within the enterprise—from public sector organizations to major banks like JPMorgan.
Many large public cloud providers offer pre-packaged AI services to businesses and organizations of all sizes. Unfortunately, these cloud providers often train their public AI algorithms on their customers’ data. Businesses may unwittingly help the competition by sharing this data to train algorithms used by other companies.
And these large-scale providers often aren’t transparent about how data will be used, which can open businesses up to potential liabilities in the event of a leak. While some sectors can tolerate this risk and embrace AI with open arms, they must still remain aware of the risks. Some industries—such as the public sector, life sciences, or even financial services—simply can’t afford these risks at all.
Privacy breaches stemming from public AI models will be catastrophic. To avoid them, organizations must be strategic and careful, limiting AI usage to areas where privacy can be better assured—or embrace vendors who emphasize a private AI approach that provides better privacy protection.
AI considerations go beyond data and compliance.
Learning about compliance and data privacy is critical to understanding the current AI landscape, but they’re not the only important trends. Recently, we interviewed eight leaders on AI trends and insights into the use of AI. Find out what they had to say: Get the Download 8 AI Experts on the Future of AI.
