AI and machine learning are revolutionising scientific prediction across fields like college admissions, elections, and drug discovery. Large datasets and complex 'black box' models are being used, with statisticians developing techniques to quantify uncertainty without understanding the models' inner workings. Concerns about reproducibility exist, and statisticians are creating safeguards for reliable findings. The emerging field of data science incorporates traditional statistics with new techniques like large-scale population tracking.
A MIT study on human-AI collaboration found that while human-AI teams often outperformed humans alone, AI systems working independently were sometimes better. AI excelled at decision-making tasks like detecting deepfakes and medical diagnosis. However, human-AI collaboration was more effective for creative tasks. The research suggests focusing on developing processes to integrate humans and AI effectively, leveraging the strengths of both.
