Artificial Intelligence & Decision Support Systems

Knowledge is the preeminent Power. It drives decisions. Artificial Intelligence (AI), since its inception, has played a revolutionary role in automating both knowledge based and non-knowledge based activities. In the current times, with the exponential growth in the processing capabilities and boom in amount of “structured data” the accuracy of AI systems to business requirements is imminent. This structured data is generated by variety of sensors being put to use in everyday devices like mobile phones, health bands, laptops etc. Though usage is limited mostly to Finance and Healthcare sectors, AI is continuously developing across various industry verticals.

The main problem in doing a knowledge work is deciding what the inputs should be so that outputs make sense. This has been overcome by using the concept of machine learning. Huge amount of data is used for generating large number of models on weekly basis, and even on daily basis, and are used for making decisions in fractional amounts of time. This has helped in earning huge revenues for firms. Humans have their capacity to do work. They have their limits and cannot be stressed beyond those limits. AI has played a pivotal role in extending these limits and maximizing profits. To exemplify, IBM Watson is providing recommendations for treatment of specific patients by bridging complex and dynamic information to generate hypotheses. This will also help in understanding diseases better and go a long way in providing customized treatments to patients. In Finance, Watson has been working as a wealth adviser and risk and compliance manager and also as a fraud detector. Financial Markets are increasingly becoming complex day by day and need vigilant and robust systems which can perform algorithmic trades, sense market trends reaping profits for organizations. AI systems can play a defining role in automating the above requirements of the financial markets pushing the current limits and taking competition to the next level.

Although there are good amount of improvements to be made in areas of natural language processing to make these systems more pragmatically used, AI systems have started to perform knowledge work and are expected to grow exponentially in the coming years with computers approaching the calculating power of human mind i.e. 20 quadrillion calculations per second and costing below $ 4000. Trust is a very important parameter which is still under research in AI. We trust a person because we know how a person thinks. The same thinking can’t be applied for these systems. One needs to balance between what systems can do and what these systems can’t do for taking maximum benefits out of AI systems.

In essence, AI systems will continuously develop in the coming years and will find wide knowledge based applications. Complete automation is not possible as this may not yield required results. However, the best application model is a conglomeration of both human decision making and AI systems to finally develop a system which can make good judgements saving more lives, making processes reliable and efficient, assist making innovative products and earning goods profits.