Artificial Intelligence (AI) is a questionable topic. Some people are suspicious about implementing this technology into daily life. However, this year has seen exponential growth in the capabilities of AI and machine learning (ML), and it is predicted that this trend will continue into 2022.
This article is partially based on the expert’s opinion of Sonia Bell. She is interested in researching in the field of marketing psychology and artificial intelligence. Sonia Bell is an expert writer in such topics as marketing, company development, and blogging.
Sonia Bell, marketing consultant and blogger
Artificial Intelligence has become so entrenched in the way we live that most people do not even register anymore that it underscores the way we communicate, travel, shop and buy services, and assist our decision-making processes in all walks of life. Self-driving cars, trucks and tractors, apps such as Siri and Alexa ordering your take out or booking your movie tickets, Netflix and Amazon presenting personalized shopping choices, and who could live without Google? It has become a household word, like Hoover in the fifties, most questions today are answered with: Just google it.
It is by far the most revolutionary technology development in recent times and is turning longstanding processes upside down. It is changing the way we do business, and claiming its benefits and pushing the boundaries of development has suitably been named the ‘new space race’.
It is a transformational development for the entire IT industry. The big companies leading the way in adopting AI is undoubtedly Amazon, Google, Microsoft, and Netflix; however, there are many lesser-known companies in the E-commerce industry that have implemented AI with tremendous success. AI enables quality services at a reduced cost, better forecasting, improved suggestions, and customer focused searching. Other industries that will soon be transformed by AI include manufacturing, distribution, construction, healthcare, education, and cybersecurity.
Whilst AI and ML (machine learning) is often used together, they are not interchangeable. Artificial Intelligence (AI) is an umbrella concept—all robotic, automated and mechanical tasks that emulate human activity qualify as AI. Machine learning is one of the subdisciplines of AI, where algorithms are fed data and allowed to learn from it and discern patterns. Natural Language Processing is another subdiscipline. Given the scope of AI, it is anticipated that different disciplines will concentrate on wide-ranging developments.
We propose the five most important and far-reaching developments in AI :
1. Automated Machine Learning (AutoML): these radical changes will smooth workflows in resolving complex problems, as it will allow programmers to concentrate on the actual problem and not having to recreate workflows for specific models. Custom ML platforms and cognitive API’s will seamlessly allineate with AutoML. Reinforcement learning used in game playing algorithms (experience-driven sequential decision-making) will take center stage in the development of applications.
Since the first step in e-business is compiling and analyzing information, data management is the most widely used application of artificial intelligence and digital automation. Robots collect, store, re-format, and trace data to provide faster, more consistent access. Such rapid development means that less human resources will be required and people will not need to use their brains to the fullest extent.
Whilst Gartner research suggests as many as 85% of CIO’s are planning AI pilots by 2020, being able to trust the results will be of paramount importance as users will use this for critical decision-making. In addition to automated machine learning, a concomitant growth in explainable AI, which will allow users to make sense of outputs and allow what-if scenarios inherent in business decision making.
2. The Internet of Things (IoT), Blockchain and AI: the improvements in cutting edge precision provided by AI can significantly improve industrial applications of IoT, especially in root cause analysis and preventive maintenance. AI chipsets that will exponentially improve the speed and execution of AI-based apps will be released by major manufacturers such as Intel, Qualcomm, and others and will assist in the development applications, in healthcare in particular. Blockchain applications, combined with AI, will see further enhancements.
3. Closer convergence between machine learning and quantum physics: quantum computing algorithms have the potential to exponentially increase the speed of certain tasks—when dealing with large amounts of data a common analysis technique is the FFT (fast Fourier transform) which is available in a quantum version. The HHL algorithm, solving a system of linear equations, is the foundation of the current quantum computing revolution, and it is extended or used as a subroutine in other algorithms.
4. ‘Smooth-talking AI assistants—new advances in natural language processing that make digital assistants capable of greater autonomy’. Bill Gates in MIT Technology Review 2019 breakthrough list Business intelligence already retrieve context driven data via cloud API’s and this trend will be enhanced by advances in the technology. Business users with no training in queries will be able to retrieve data seamlessly from AI driven BI programs.
5. Privacy, accountability, and ethics in AI: Valid questions on a bias, ethics, privacy, and accountability being raised by numerous groups and researchers has resulted in several initiatives and control bodies being established. The next years will see an increase in governance frameworks, covering standards and policies around legal accountability, values, privacy, security, transparency, ethics, and abuse of power.