Artificial Intelligence

Artificial intelligence (AI) involves programming computers to complete tasks that typically require human intelligence, such as comprehending language, making decisions, and solving problems. This broad term encompasses a number of technologies, including predictive AI, generative AI, large language models, and machine learning. AI is evolving at an exponential rate and is thus transforming a range of industries, from healthcare to finance to transportation.

AI has the potential to create meaningful innovations that improve the lives of older adults. For instance, AI powers automated vehicle technology that will eventually lead to fully self-driving cars. This can expand access and reduce isolation for people who do not drive, including some older adults (see also Vehicle Automation and Fully Self-Driving Cars). AI also powers digital assistants. And it is transforming health care, financial services, and other sectors of the economy (see also Privacy, Confidentiality, and Security of Health Information).

Consequential decision-making: AI systems are being used to make or inform consequential decisions. Consequential decisions are those that have a significant legal, material, or similar impact on an individual's life. For example, AI can be used to make recommendations about whether someone:

• is offered a job;
• is approved for housing;
• receives access to credit, housing, insurance, and financial products—and at what price;
• receives various health services; and
• is eligible for government benefits.

AI may be trained using data that includes biased human decision-making. This produces biased AI decisions. The potential for adverse outcomes resulting from the use of AI is disproportionately high for groups that are discriminated against.

For example, if AI is trained using health data sets of mostly white individuals, people from communities of color may not receive appropriate health care (see also Health Information Technology). Another example is the use of AI in hiring, in which the AI is trained using data from a time when people age 60 and older were routinely excluded from the hiring process. This could lead to applicants age 60 and older being left out of the hiring pool, inadvertently perpetuating ageism in hiring practices (see also Strengthening Laws and Practices Against Age Discrimination).

Safeguards are needed to ensure that the use of AI does not perpetuate historic and ongoing societal prejudices, including against older adults. Doing so could actually result in less biased decisions than in human decision-making.

Policymakers and the private sector also have a key role to play in preventing the misuse of AI. For example, generative AI can create very convincing deepfakes that can be used to commit fraud against older adults (see also Scams and Fraud). Similarly, predatory lenders, such as those offering payday loan products, could use AI to better target consumers who are having difficulty making ends meet. The high fees and annual percentage rates of these loans could make consumers worse off (see also Alternative Financial Services).

Policy framework: Issues such as discrimination, fraud, disinformation, and harmful financial practices are not new. However, they are manifesting in novel, more targeted, and more expansive ways because of AI. Moreover, given how inexpensive and easy it is to use, AI can cause damage at a scale that was previously difficult to achieve. The challenge, then, is how to support and encourage positive uses of AI while protecting against its potential negative effects and applications. 

One difficulty is the recruitment and retention of government staff with the technical knowledge to be able to effectively provide oversight of the industry. This can be overcome by allocating more resources to agencies, enabling them to build their expertise. Another challenge is that AI is evolving much faster than the slow-moving legislative and regulatory processes. To combat this, policymakers, consumer groups, industry groups, and other leaders can work in partnership to create dynamic and flexible standards that promote both innovation and consumer protection. This approach can lead to a regulatory system that remains relevant as AI evolves.