Political Scientists

However, many political science tasks still need people. AI may miss context or nuance – for example, an AI poll gave wrong answers about the Ukraine war because it lacked up-to-date information ^[4]. Systems like Elicit often need a researcher to guide them and correct mistakes ^[3].

Higher-order tasks – picking research topics, developing new theories, interpreting complex laws, teaching students – rely on human judgment. In short, AI can handle routine data processing and fact-finding, but experts are still needed to think critically about what the data mean and to teach, debate, and form policy recommendations.

On the other hand, adoption may be slow or cautious. Political analysis often deals with sensitive or fast-changing issues, so accuracy and trust are critical. Experts found that AI “agents” gave plausible answers on many survey questions but failed on some new topics – highlighting that models need careful updating ^[4].

Many analysts expect AI will augment rather than replace people (for example, combining AI polling with real human surveys) ^{[4] [3]}. There are also ethical and legal concerns: e.g., bias in AI, privacy of data, and public acceptance of “computer” input on policy. Building custom AI tools can be expensive, and institutions may move slowly to adopt them.

Overall, AI is a helpful tool in political science (especially for labor-intensive tasks like data processing), but human skills remain at the core. Young political scientists who learn to use AI wisely can be more productive, while still applying creativity, critical thinking, and teaching – things that machines cannot do on their own ^{[4] [3]}.