Introduction
Artificial Intelligence is a technology that allows machines to learn from experience, adjust to change, and perform tasks that humans currently do. From its early beginnings in the 1950s, AI has evolved over the years to handle increasingly complex and varied tasks. There are two types of AI: narrow and general. Narrow AI, sometimes called weak AI, performs a single task extremely well, such as facial recognition or identifying the best music to play next. Narrow AI may be able to outperform humans at some tasks, but it's never going to be a match for a human's general intelligence. The milestone for General AI is when a machine can perform any intellectual task that a human can do.
AI has made sweeping strides in recent years, leading to machines that can drive cars or chat with us in natural languages. Soon, AI will connect to and control other machines around us. AI will also connect with many robots, networks, and even drones with which we will communicate. It's only a matter of time before AI becomes the primary line of communication in our homes and businesses. On one end of the spectrum, enthusiasm about AI and its abilities to improve our lives is on the rise, with many technologists, corporate leaders, and government officials readily predicting that the impacts of AI on employment and productivity will push economic frontiers beyond today's record highs. On the other end, there are fears for the millions of people whose jobs will now become automated, leaving them without employment. There are also fears that more complex AI will only add to the wealth gap. This text is intended to provide readers with a balanced perspective on AI's potential effects. Its purpose is to show readers how to apply AI in their lives and organizations in order to be ready for the future. The framework for this discussion includes the cons, the pros, followed by a set of summarized pros and summarized cons.
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The Pros of AI in Society
The vast array of applications and impacts of artificial intelligence (AI) in society has the potential to transform set practices and mindsets. Especially important to organizations are the efficiency gains from the maximization of big data at a relatively low cost; a survey of trade professionals across the UK covering a wide sector of organizations found that only 4% of respondents used AI or robotics in their day-to-day operations. However unnatural, it is inevitable that automation is here to stay; the workplace responses highlighted relative cost savings, data entry, customer service, and wasting less time as the key uses of AI.
Primarily, AI has the ability to analyze large data in a fraction of the time and cost that employees would take in finance, healthcare, and social influence, including marketing and user experience. Moreover, AI can contribute to promoting intrinsic satisfaction to attract and maintain user engagement, from customer experience to personalized gaming. Furthermore, AI applications such as chatbots can fix simple queries, reports, or complaints without any human intervention and thus leave humans to solve more complex or emergency cases as they arise. Given the well-designed, common-sense parameters of AI application, it could help improve the diversity of GDP and proportionally increase gender balance in this high-earning population. AI, when underpinned by certain values and drivers, has the scope to enhance capital allocation to help realize the SDGs by 2030.
The Cons of AI in Society
From an algorithmic perspective, the primary downside to AI in today's society is that it puts our privacy at risk. AI requires large amounts of data in order to provide value; as a result, we must have a great deal of faith in system developers' commitment to data protection. When data protection is out of control, we put entire societies of individuals at risk. Another common problem with AI is its potential for bias. AI systems are merely algorithms that search for patterns in data. A lack of attention to such errant data appears straightforward but has substantial consequences. For instance, the police in Detroit began operating a facial recognition surveillance network in 2017. When putting people away into the jails, seventy-six of the individuals profiled as members of the community had their charges abruptly dropped.
One significant concern if we are to depend on machines to make vitally important decisions for us is the ethics of it. The key issue here is the machine having the knowledge and the wisdom—a result of having learned good ethics and, at least, a basic understanding of the history of humanity. Another significant issue with the widespread adoption of AI in society is the threat it poses to employment. The industries hit hard by the earliest of automations will adapt and reduce their earnings. Many workers in these industries will remain jobless because they are no longer needed. There is now an oversupply of workers for the new jobs in the markets, which creates a differential bargaining advantage for companies over labor, giving firms the ability to pay lesser wages for the work that needs to be done. Artificial intelligence machines replacing workers are placing themselves in the exact same category of being last on earth. With recent downturns in industries, some companies will start to hire again while being more selective with their hires. Research, however, suggests that these jobs will never come back, or at least not fast enough to support all workers dislodged from manufacturing in time or education. Even in the case of jobs coming back, just eventually is too long of a time period for our workers to undergo the process of changing. This is due to the impression that displaced blue-collar workers will likely never adjust to new labor skills.
Conclusion
In this review essay, we have addressed the positive and negative aspects of AI, which shape today’s society. AI has the potential to improve our personal lives, economies, and industries such as financial services and healthcare, and to provide insight to social scientists and policymakers. Despite these advantages, we have identified significant questions regarding how AI should act and who will be in control of it. We have discussed a number of potential negative impacts, which could leave AI in general and machine learning in particular broadly as a force for retrenchment, further entrenching today’s problems of inequality and injustice.
We have identified how existing economic models of 'superstar' markets can be disrupted further by AI and machine learning, and analyzed the possibility of their subsequent regulatory and legal problems. In the justice markets and systems, current problems of bias could be further entrenched by machine learning models, and we have shown how many models already in use demand greater attention and ethical reflection than has typically been given. Recent reports on ethical AI in professional services did provide some initial steps towards regulatory models that might balance the public interest against continued innovation, and we have suggested some additional ways to find those crucial balance points.
Finally, we have indicated some potential future directions for AI technology, which could further constitute how our societies are structured. Our essay suggests that AI is at a tipping point, having proved its value sufficiently to become part of the world’s technological wealth. We consider it to be critical that AI be a force for creating – albeit radically – a more equitable and just society that we all want to live in. To do this, it is essential that a range of stakeholders, including social scientists, ethicists, the general public, policymakers, and commercial engineers and developers, work together in the co-production of responsible innovation in AI. They must engage with governance implications and support the further development of monitoring technologies that oversee AI.
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