Artificial Intelligence (AI) has the potential to disrupt the world as we know it. Self-driving cars, relationship apps, facial recognition, cybersecurity and use of robotics in healthcare are only a few examples that we are already familiar with, through which AI is already changing our world.
In simple terms, modern AI systems have evolved from machine learning protocols capturing and processing data related to their environment in real time, to processes making optimal, real-time decisions towards specific objectives. Initially conceived as a technology that could mimic human intelligence, the technology has evolved in ways that far exceed original perceptions. Thanks to intelligent machines allowing for high-level cognitive processes like thinking, perceiving, learning, problem solving and decision making, coupled with advancement in data collection and aggregation, analytics and computer processing power, AI presents opportunities to complement and supplement human intelligence and enrich the way people live and work.
AI is no new phenomenon. Having been a technology-in-progress for the past 70 years, the first application can be attributed to the development of the electronic computer in 1941 and the stored program computer in 1949. In the 1950s US mathematician Norbert Wiener was one of the first to theorize that all intelligent behaviour was the result of feedback mechanisms, which mechanisms could possibly be simulated by machines.
Thanks to ever increasing computing power, the decreasing costs of data storage, and the massive amount of data that is being digitized, AI is set to develop at an exponential rate, both in terms of application and reach, as organisations learn to unlock the untapped value of cross mapping vast volumes of data.
As laid out by Kate Crawford and Meredith Whittaker, co-chairs of the AI Now symposium held in July 2016, AI can be assimilated to a “constellation of technologies”; a symbiosis of machine learning, perception, reasoning, and natural language processing that enable machines to mimic certain human capabilities of sense, comprehension and act. For instance, computer vision and audio processing systems can actively analyse the environment around them by acquiring and processing images, sound and speech, whilst the natural language processing and deduction engines can enable AI systems to analyse and understand the information collected. An AI system can also act through technologies such as inference engines or undertake actions in the physical world. These capabilities are augmented by the ability to learn from experience and keep adapting over time. AI systems are finding ever-wider application to supplement these capabilities across enterprises as they grow in sophistication.
AI has slowly been working its way into businesses. Business Intelligence (BI) systems generate and automatically process a wealth of digital data providing the necessary metrics to efficiently run an organization. Machine learning and AI solutions have the potential to further crunch such data creating unprecedented opportunities for improvement across health, lifestyle, transportation, education and practically every human activity.
Governments across the globe are also becoming increasingly aware of the potential economic and social benefits of developing and applying AI. For example, China and the UK estimate that 26% and 10% of their GDPs respectively in 2030 will be sourced from AI-related activities and businesses [source: diginomica.com]. There has also been tremendous activity concerning AI policy positions and the development of an AI ecosystem in different countries since 2017, with the US, France, Japan, the UK and China being amongst the first to take the lead by publishing the first ideas for an AI national strategy.
Malta is also set to jump on the bandwagon, having recently announced its plans to develop a National AI Strategy by 2019, aimed at putting the island amongst the top 10 nations that have taken such an approach. A key advantage of Malta is its size, making it similar to a cosmopolitan city that could allow companies to test their products in a real-life scenario.
Proper implementation of AI globally will also require a comprehensive regulatory framework. As AI applications engage in behaviour that, had it been done by a human, would have social and civil legal consequences, the judicial and legislative stakeholders need to develop the necessary regulatory infrastructure to determine whom to hold accountable, substantiated by ancillary principles of social justice. Given how deep and far-reaching AI’s impact on one’s everyday life, thorough appreciation of ethical principles and legal clarity are a necessity. For instance, potential investors need to know what will happen when things do not go according to plan. Differences are to be drawn between self-executing AI systems and agent AI systems engaging in activity on its owner’s behalf; a private individual using SIRI or a brokerage firm deploying a robotic advisor that uses algorithms to buy and sell securities.
As technology is being deployed as a core element in businesses and society, governments and the community at large have to recognize, acknowledge, and fully understand the ramifications of how AI can transform society. As with all revolutions and disruptive technologies of recent times, there are obstacles to overcome. Some businesses, governments and organisations investing in the technology will inevitably prosper, whilst others will fail. Those that manage to succeed will be those that manage to see beyond the hype and truly understand how this technology can add real value and drive positive change.
Should you wish to explore how to harness these developments in AI, contact Grant Thornton’s advisory team to help you unlock your business’s potential through digital transformation.