Human Augmentation of AI – the way Forward!
To progress as whole, holistically, as an advanced knowledge community, beyond boundaries, “Learning” accomplished either by Human or Machine has to be measured, objectified, quantified, qualified, summarized, contextualized, governed, actualized and lived. Many human discoveries were also because of organization of knowledge, best example I could think of could be Periodic Table, which lead to explore further in what other elements in element table, and if found what would be their characteristics, when observed where it can be used, how it can benefited for Humanity. From constant feed of the world wide happenings around AI, people participating in AI, our understanding into the AI advances, we can start to see them in different layers. Its primarily important to recognize distinctively ‘Where?, What?, How?’ to make contextual sense. Where could be which vertical, Healthcare, Education, Social. What could be which problem/sub problem it is getting addressed, or Use-Cases, Value. How could vary in different levels of rigor of understanding the underlying research, frameworks which enables them and specific but larger issues that it could address if it solves well.Though these are pointed trends and sub trends, “Select a data science/ artificial intelligence trend and describe it’s potential impact (e.g. automated machine learning, up-skilling and data literacy, improvements in facial recognition, increased data privacy laws, democratization of data visualization tools, other trends) “, basically knowing them well in the context of adopting approximate modelling algorithms to extract signals or patterns out of data produced by human, the focus is to progress, whats required is not more capable machines or a break through algorithm but Human Understanding of context of these Machine Learning Algorithms, How they go about learning patterns, When put into use, What Issues and Impacts it will create for Humans, is the active discussion be it World Economic Forum, DOD or GAFAM, while leveraging AI as a tool. Human Augmentation of AI is the way Forward! DOD AI Ethics Principles – Responsible, Equitable, Traceable, Reliable, Governable, Value AI Needs to Respect – Explainable, Fairness, Reliability and Safety, Privacy and Security, Inclusiveness, Transparency, Accountability. In leading the “AI journey together”, recognizing the need for Human Augmentation, exchanging know how and happening around AI, connecting people and exchanging perspectives around ai, driven by Human catalyst like “storybydata” platforms and many other such efforts eases and make all of us progress faster with clear visibility. Learning from Humans, about marvels of AI machines, how they learn from Human Data.
Author – Madhusoodhana Chari S