Technology and the Future: The Rise of Artificial Intelligence

Today, the proliferation of artificial intelligence (AI) has revolutionized numerous industries through automation of a wide array of labor-intensive tasks, as well as through the facilitation of the decision-making process in ways that encourage innovation. To learn more about these game-changing technologies, this essay explores the positive and negative impacts of AI technologies on individuals and groups from the perspective of Immanuel Kants deontology. A deontological approach is particularly relevant for this type of analysis because it focuses on the adherence to ethical principles and the intrinsic morality of actions including a so-called duty of beneficence to act in the interests of others to maximize present and future benefits while minimizing harms for all stakeholders (Mansell, 2019). Using this approach, the essay examines the historical context of AI technologies and an analysis of what is currently taking place as increasing numbers of public and private sector organizations seek to leverage their benefits while minimizing the corresponding adverse impacts. Finally, an analysis of the future implications of AI is followed by a series of recommendations concerning the use of these technologies in the future. A summary of the key points that emerged from the research are provided in the essays conclusion.

Historical Context

In reality, the concept of artificial intelligence has roots dating back to classical philosophers who explored the idea of mechanical reasoning. Modern AI, though, began to take shape during the mid-20th century when Alan Turing proposed the Turing Test in 1950 as a measure of machine intelligence (Saha et al., 2024). The official birth of AI as a field of scientific study, however, is traced to the 1956 Dartmouth Conference (Moor, 2016). At this conference, Professor John McCarthy brainstormed proposals with a few colleagues for the future use of these technologies (Artificial Intelligence Coined at Dartmouth, 2024).

While the Dartmouth Conference helped generate increased interest and funding for AI research during the 1960s, this initial level of enthusiasm diminished in the following years resulting periods of so-called AI winters (Chun & Elkins, 2022). As computer processing speeds continued to follow the dicta of Moores Law, though, there was a resurgence of interest in newly developed expert systems during the 1980s as well as significant breakthroughs in machine learning during the 1990s (Chun & Elkins, 2022).

Given these sustained improvements in computer processing capacities, it is little wonder that the 21st century has witnessed exponential growth in AI capabilities, driven by increases in computing power, the increasing availability of big data and significant improvements in algorithmic designs (Asker et al., 2022). Besides routinely passing the Turing Test at present, other notable advancements in AI include the supercomputer Deep Blue. Developed by IBM, Deep Blue was already capable of processing 200 million different chess moves per second in 1997, a capability that allowed it to defeat the then-world chess champion, Garry Kasparov, in 1997 (Deep Blue, 2024). More recently, Googles AlphaGo likewise succeeded in defeating the worlds top Go player in 2016 (Ribeiro, 2016). In other words, the past 75 years in AIs history have mirrored the remarkable success of aviation in moving from modest beginnings to infinite possibilities for the future, resulting in a current situation that holds even greater promise for the future as discussed further below.

Current Situation

The cumulative effects of the benefits of AI have already translated into multiple impressive benefits for humankind, including most especially in automation of complex tasks and healthcare applications where AI has demonstrated its ability to help diagnose illnesses and perform delicate surgical procedures (Lutenco et al., 2024). Other innovations in AI technologies including autonomously driven vehicles, including...

2. Universal Ethical Standards: Given the increasing ubiquity of AI technologies, a second recommendation is to develop universal ethical standards which can serve as an ethical framework that ensures moral principles are taken into account which protect humans in addition to any economic calculus that may drive their use.

3. Non-Discrimination: Similar to universal ethical standards, deontological ethics requires that engineers design AI systems so that they are fair and equitable in their algorithmic-based decision-making processes without unintentional bias that may discriminate any some demographic, social or political groups. Indeed, Google is currently facing harsh criticism for this very issue with respect to its search results for the ongoing presidential election.

4. Education and Informed Consent: Finally, it is essential to ensure that everyone who interacts with AI systems fully understand the nature of the exchange so they can confirm their informed consent in some type of positive fashion.

Conclusion

The research showed that the AI genie is out of the bottle and there is no turning back. The rapid advancement of artificial intelligence has ushered in a new era of technological innovation, bringing both unprecedented opportunities and complex ethical challenges. Using a deontological perspective, this essay examined he historical context, current situation, and future implications of AI, with an emphasis on the importance of conforming to ethical principles that respect human autonomy. The research was consistent in showing that as AI continues to permeate various aspects of our lives, from healthcare to transportation, it is crucial to address the ethical concerns it raises. The recommendations provided provide a useful, but not exhaustive, framework for responsible AI development, deployment and use. These recommendations emphasized the respect for human autonomy, the establishment of universal ethical standards and the importance of informed consent to maximize the benefits of…