STEM and AI: shaping the future of the STEM industry

Artificial intelligence is reshaping the world at an unprecedented pace, and nowhere is this transformation more visible than in STEM — science, technology, engineering, and mathematics. Together, STEM and AI are creating powerful new possibilities for research, innovation, and real-world problem solving.

From healthcare breakthroughs to advances in climate science, AI is driving progress across the STEM industry. At the same time, platforms like Outlier are giving domain experts new ways to contribute their expertise and shape the future of AI. 

What is STEM in AI?

STEM in AI is the intersection where human expertise in science, technology, engineering, and mathematics helps guide and improve artificial intelligence systems.

Consider AI in STEM applications: a mathematician refining problem-solving logic, or an engineer helping evaluate AI’s ability to model real-world systems. These are not abstract ideas — they’re the foundation of AI training work happening today. Large language models (STEM LLM) in particular rely on structured knowledge and critical feedback from experts.

In other words, STEM provides the rigor, while AI brings the scale. Together, they form a feedback loop that accelerates discovery and innovation.

The current STEM industry and AI

The STEM industry has always been a driver of progress. Today, it is increasingly powered by AI. Algorithms assist researchers in analyzing vast datasets, simulations accelerate engineering design cycles, and machine learning supports breakthroughs in medicine. According to the National Science Foundation, federal investment in AI-driven STEM projects has grown significantly in recent years (source: National Science Foundation).

AI is also at the center of STEM news — from genome editing tools trained with predictive modeling to AI-powered climate forecasts. These developments showcase how STEM development is expanding with AI as its catalyst.

At the same time, domain experts remain essential. Outlier Experts, for instance, review AI-generated responses, test logic chains, and help refine reasoning. Their feedback ensures models are not just intelligent but accurate, ethical, and aligned with real-world knowledge.

STEM technology: how AI is driving change

The integration of AI into STEM technology is transforming entire disciplines.

• Engineering: AI is used to optimize designs and test prototypes in simulated environments, reducing costs and accelerating innovation.

• Mathematics: Generative models are capable of assisting with problem sets, while experts ensure accuracy by evaluating outputs and refining the underlying logic.

• Science and data analysis: AI expands predictive modeling, whether in epidemiology, particle physics, or astrophysics.

These examples show how AI supports STEM development by making research more efficient and scalable. Yet, it’s only possible with expert input. Outlier Experts are matched with opportunities where they evaluate AI performance, ensuring results are valid and reliable.

For those with advanced math expertise, Outlier even offers projects focused specifically on problem-solving tasks. 

The future of STEM with AI and LLMs

Looking ahead, the future of STEM is inseparable from AI innovation. Large language models and other generative AI systems are rapidly evolving, opening up new ways to conduct research, teach complex concepts, and support cross-disciplinary collaboration. The World Economic Forum notes that AI will be central to the evolution of STEM education and workforce development (source: World Economic Forum). 

For example, an STEM LLM could help researchers translate findings across languages, or provide real-time data interpretation in a laboratory. In classrooms, AI-powered tutors may personalize STEM education at scale, offering students adaptive challenges tailored to their learning pace. For Outlier Experts, this means being directly involved in the future of STEM while shaping AI responsibly.

Outlier’s role in STEM and AI development

The role of Outlier in this landscape is unique. By connecting experts to AI training tasks, Outlier ensures that the next generation of AI systems is built on accurate, domain-informed knowledge.

Opportunities range from math-based problem solving to evaluating technical explanations in engineering or science. For example, experts may be matched with a project where they:

• Review AI-generated reasoning in STEM-related prompts.

• Evaluate multimodal data, ensuring AI correctly interprets charts or graphs.

• Provide nuanced feedback on specialized terminology in their field.

Unlike traditional roles, these are flexible part-time opportunities that allow Outlier Experts to contribute while balancing research, study, or professional responsibilities. 

How to get involved in AI training with Outlier

Joining Outlier as an expert is straightforward, and it allows you to actively shape the future of AI while staying rooted in STEM. As an Outlier Expert, you’ll:

• Be matched with projects aligned to your expertise.

• Become familiar with project guidelines before tasking.

• Complete tasks and receive payment based on your contributions.

• Engage with the supportive Outlier Community.

As AI continues to evolve, the relationship between STEM, AI and expert contributions will define the next wave of innovation.If you’re curious about how the process works, check out Your guide to working on Outlier.

FAQs

What is STEM in AI?

It refers to the integration of science, technology, engineering, and mathematics expertise into artificial intelligence systems. Experts guide AI models with domain knowledge, ensuring accuracy and reliability.

What does STEM stand for?

STEM stands for science, technology, engineering, and mathematics.

How is AI used in STEM education?

AI supports personalized learning, automated grading, tutoring systems, and virtual labs. Instructors use it to create adaptive lessons that respond to students’ strengths and weaknesses.

Will STEM jobs be replaced by AI?

AI is not replacing STEM jobs but reshaping them. Many tasks are automated, but this creates new opportunities for experts to guide, evaluate, and refine AI systems within the STEM industry — a trend often highlighted in STEM news.