Is Generative AI mature for alternative image descriptions of STEM content?

Alternative descriptions of digital images have always been an accessibility issue for screen reader users. Over time, numerous guidelines have been proposed in the literature, but the problem still exists. Recently, artificial intelligence (AI) has been introduced in digital applications to support visually impaired people in getting information about the world around them. In this way, such applications become a digital assistant for people with visual impairments. Increasingly, generative AI is being exploited to create accessible content for visually impaired people. In the education field, image description can play a crucial role in understanding even scientific content. For this reason, alternative descriptions should be accurate and educational-oriented. In this work, we investigate whether existing AI-based tools on the market are mature for describing images related to scientific content. Five AI-based tools were used to test the generated descriptions of four STEM images chosen for this preliminary study. Results indicate that answers are prompt and context dependent, and this technology can certainly support blind people in everyday tasks; but for STEM educational content more effort is required for delivering accessible and effective descriptions, supporting students in satisfying and accurate image exploration.