Jakub Langr, cofounder of brainpool.ai, a network of AI experts, and a guest lecturer at Oxford, recently wrote a post on Forbes.com about how Generative Adversarial Networks (GANs) are shaping the future of AI.
One of the most promising innovations of AI, GAN enables creativity in AI development. GANs can produce a painting as if it were the work of a creative and skillful painter. Langr also listed GAN’s applicability in other sectors, among them, helping cancer detection by creating new, realistic scans and applying both defensively and offensively in cybersecurity. GAN is one of the areas of AI that are “growing by leaps and bounds every six months”.
“But with the ability to generate new data or imagery, GANs also have the capacity to be dangerous”, Langr noted, as they can create fake contents that look real. Therefore, “ethics is a key topic “, which is covered in his book, “GANs in Action: Deep learning with Generative Adversarial Networks”.
The article raises the need to define public AI policy more than the public perception of AI and its dangers. The industry should play a more active role in this matter. If good public AI policies are in place, GAN will be one of the brightest hopes in shaping AI innovation, serving people in an ethical way.
Boston Global Forum and Michael Dukakis Institute for Leadership and Innovation generated the AI World Society (AIWS) Initiative 7 Layer Model, and GAN could play an important role in creating applications of layer 6 and layer 7 of the model.
