Problems and opportunities of artificial intelligence

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Gürsakal, Necmi
Çelik, Sadullah
Batmaz, Bülent
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İnönü Üniversitesi
This article reviews Artificial Intelligence (AI)’s challenges and opportunities and discusses where AI might be headed. In the first part, it was tried to reveal the differences between Symbolic AI and Deep Learning approaches, then long promises but short deliveries of AI were mentioned. The problems of AI are that the media has high expectations about artificial intelligence and keeps the problems and restrictions it creates low. Today, while AI is stuck with issues such as deepfake applications and carbon footprints that create moral and climatologic problems; on the other hand, it is struggling with problems such as deep learning models requiring huge amounts of data. Another problem with deep learning is that deep learning models are a blackbox and not open to improvements because it is not known where mistakes were made. Among the new paths ahead of AI are Hierarchical Temporal Memory (HTM) models and hybrid models that generally try to bridge the gap between Symbolic AI and Connectionist AI. If we consider that the most important leaps in AI have been made with the features of the brain that AI can imitate, then the developed HTM models may also be a new opportunity for AI.
Hierarchical temporal memory , Deep learning , GPT-3 , Black-box , Carbon footprint
Gürsakal, N. , Çelik, S. & Batmaz, B. (2022). Problems and opportunities of artificial intelligence. Akademik Yaklaşımlar Dergisi, 13(1), 203-225.