Integration of Artificial Intelligence Inevitable

As the data-driven world marches towards the unprecedented fourth industrial revolution, machine learning, and artificial intelligence technologies have mainstream. Although AI emerged in the 1950s, it’s until 2001 when AI technologies started to surge on the market (Russell and Norvig 17). AI has increasingly become part of human’s life affecting people’s interaction, work, travel, and shop. AI is no longer science fiction and its application has no limits. Notable tech leaders reiterate AI as ubiquitous innovations in history. Google CEO, Sundar Pichai, asserts that “AI is one of the most important things humanity is working on. It is more profound than, I don’t know, electricity or fire,”.
From simple virtual assistant devices such as Amazon Alexa to Uber’s self-driving cars, medical diagnosis to the autonomous weapon, AI adoption is rapidly taking hold worldwide with potentially revolutionary effect. Although AI is yet to realize wide-scale commercial deployment, companies that build or utilize AI are growing exponentially. The World Intellectual Property Organization (WIPO) estimates a 6* increase in Venture Capital investments in AI startups and thousands of AI startups multiplying by 14* since 2000. WIPO reports accelerated growth in AI invention patents amounting to 340,000 and over 1.6 million scientific publications. Statistics forecast that AI will contribute 26% growth of the global income by 2030 (WIPO). From adoption by multinational corporations such as Tesla, Microsoft or Shell to startups such as Soundhound or Megamind, AI has been streamlined in today’s business.
Artificial Intelligence is the simulation of human-like- intelligence and processes such as learning, reasoning and corrective action by coded software are entailing detailed instructions (Russell and Norvig). The algorithms coded by software enable machines to perform myriad of tasks such as complex patterns recognition, information synthesis, deriving conclusions and forecasting. AI is a data-driven technology that is applicable in diverse industries. The influential trajectories of AI include neural networks, robotics, and symbolic systems. AI adoption is high in sectors that are strong digital adapters such as telecom, automotive and financial sectors, and low in sectors such as education, healthcare, and tourism while remains modest on retail and media companies. The discourse on the potential implication of Artificial intelligence (AI) remains equivocal. One strand of discourse arguing that leveraging AI will lead to the downfall of humankind by surpassing human intelligence which remains the most powerful known biological technology while another strand of discourse posits that AI would generate a positive transformation of the word (Acemoglu & Restrepo32).
Artificial intelligence (AI) sustains both social and economic life by solving inherent challenges in society. AI augments growth through three pathways; intelligent automation, capital and labor augmentation, and innovation diffusion. Antithetical to the traditional automation approach, AI is capable of self-learning, which enables adaptability and agility of automated complex tasks which optimizes output. AI has been instrumental in revolutionizing manufacturing. By eliminating redundancy and downtimes on machine operation in the manufacturing sector, AI bolsters business profitability. Industrial robotics performing such as automated customer services reduce business operation cost while boosting sales. AI has been instrumental in the production of a self-optimizing manufacturing system where modular components powered by IOT and sensors enable the performance of multiple tasks.
AI is unleashing a new wave of climate-sensitive technologies. Start-of-the-art renewable energy projects such as wind energy, solar energy, hydro energy, and hybrid energy models have been inspired by big data supported by AI. Eco-design and green design innovations using the principles of AI t have aided in lowering human society high dependence on ecosystem services reducing the human environmental footprint (Aversa et al.). The impact of AI on healthcare are promising. From clinical research, disease diagnosis to drug development, application of AI in health care has yielded a revolutionary effect. Financial and medical benefits accrue from precision surgery, automated operations, and preventive medical intervention enabled by AI technology. Health care projects such as the DeepMind Health project launched by Google leverages AI in retrieving medical records to fastback service delivery. An AI-powered cognitive health assistant program “Medical Sieve” by IBM enables precision in analyzing radiology images (Mesko).
AI is associated with an alarmist perspective that centers on the unemployment effect of automation. However, the productivity effect of AI automation is twofold. Acemoglu & Restrepo6 argue that while automation resulting from the integration of AI yields labor displacement effect, on the other hand, automation optimizes on productivity for a unit of resource invested, Subsequently, cost of production declines which is reflected in lower prices of products enabling households to be effectively richer, increasing demand for goods and services. Moreover, automation yields capital accumulation ultimately increasing demand for labor and real income, hence AI yields productivity effect as opposed to displacement effect in the labor market. The rapid capital accumulation in the early 20th century realized in the American economy and British economy as a result of automation provides is a clear illustration of the productive effect of AI technology in an economy (Acemoglu & Restrepo6). North withstanding, AI will result in the creation of a new cadre of jobs through new business models. AI system developers, trainers and performance monitors are some of the new and direct job categories created by the firms using AI. For example, the introduction of data powered cab sharing services has been identified to increase the demand for taxi services by reducing the cost of the services as opposed to reduce the number of taxi drivers on the road.
AI is not without existential limitations. Infusion of AI will disrupt a country’s occupational structure. An Oxford Review of Economic Policy by Levy cautions that the potential populist politics resulting from AI integration. Populist politics along the lines of nativism and economic losses were evident in the US 2016 presidential elections where the loss of manufacturing jobs in the US was linked to the earlier political policy that enabled Chinese Imports demonstrating the populism risk that Occupational polarization triggered by AI (Levy). Over the decades, humans have maintained unsafe tendencies that pose insecurity to themselves and others, and the advent of AI compounds the challenge. A fundamental criticism against AI is ethical issues. AI- enabled vulnerabilities such as information manipulation could potentially trigger AI-influenced cyber conflicts. AI would revolutionize cyber-attack by enhancing g precision and speed which maximizes on disruption. Currently, there exist no computer control systems that would directly pause harm to humans but with the increasing assimilation of the internet of things (IOT) and automation, such systems are inevitable and would create a global catastrophe. Distinctive catastrophic scenarios such as an erroneous military command of massive attack AI robots, computerized autopilot planes crashing on nuclear plants, hacking automated factories to produce toxic chemicals, large scale infrastructure failure, manipulation of human behaviors through computer virus among present plausible danger of AI. Turchin & Denkenberger identifies the online suicide challenge “Blue Whale” that leftover 130 Russian children dead as a catastrophic scenario demonstrating the evident cybersecurity risk of interconnectivity powered by AI technologies.
Indisputably, the future will be based on autonomous systems – machines powered by AI as the world navigates the fourth industrial revolution. Therefore, it’s imperative to formulate global AI polices that ensure that research and development on AI technologies focuses on the optimization of social good.


Work Cited
Acemoglu, Daron, and Pascual Restrepo. Arti?cial Intelligence, Automation and Work. p. 42.
Aversa, Raffaella, et al. “Biomimetic and Evolutionary Design Driven Innovation in Sustainable Products Development.” American Journal of Engineering and Applied Sciences, vol. 9, no. 4, Apr. 2016, pp. 1027–36. DOI.org (Crossref), doi:10.3844/ajeassp.2016.1027.1036.
Mesko, Bertalan. “The Role of Artificial Intelligence in Precision Medicine.” Expert Review of Precision Medicine and Drug Development, vol. 2, no. 5, Sept. 2017, pp. 239–41.
Russell, Stuart, and Peter Norvig. Artificial Intelligence: A Modern Approach. 3 edition, Pearson, 2009.
Turchin, Alexey, and David Denkenberger. “Classification of Global Catastrophic Risks Connected with Artificial Intelligence.” AI & SOCIETY, May 2018. DOI.org (Crossref), doi:10.1007/s00146-018-0845-5.
Wipo Technology Trends 2019 - Artificial Intelligence. World Intellectual Proper, 2019.