Mastering artificial intelligence (AI) doesn’t necessarily require technical skills. Complex systems like AI can be better understood and developed through diverse learning methods. A multidisciplinary approach, combining humanities and sciences, is crucial for AI development. This is because AI systems aren’t just about algorithms and data, but also involve understanding human behaviour and societal impact.
AI education is shifting to include people from non-technical backgrounds. This shift helps to broaden AI’s potential applications and the range of problems it can solve. AI is increasingly used in fields like healthcare, finance, and logistics, which require domain-specific knowledge. Therefore, professionals from these fields can contribute to AI development by providing this knowledge.
The rise of no-code AI platforms allows non-technical professionals to create AI models without coding. These platforms provide an intuitive interface and pre-built models, enabling users to build, train, and deploy AI models. However, these platforms still require an understanding of AI principles and the ability to interpret results.
AI education should focus on teaching these principles and interpretation skills, rather than just technical skills. This approach can create a more diverse AI workforce, capable of solving a wider range of problems. It can also help to address AI’s ethical issues by including perspectives from different fields and backgrounds.
Go to source article: https://www.zdnet.com/education/professional-development/master-ai-with-no-tech-skills-why-complex-systems-demand-diverse-learning/