How far should humans be allowed to proceed with artificial intelligence?
With AI developing at a frenetic rate, the question of how far humans should be permitted to go
with AI has emerged as an urgent ethical concern. Artificial intelligence is not inherently good or evil, but
there are pros and cons to using it. Furthermore, it is only fair that humans be given the freedom to push
AI to its limits, with the goal of maximizing advancement and creativity while minimizing hazards. "AI has
been around since the 50s, so it's not like the research has just happened. But the discussion now is
because we realized that AI is impacting nearly every sector of society. "And so, because of that, these
technologies then have been thrust upon the public and now the public is standing up and saying, 'What
are we doing about trust? (Andrews, 2023) The question remains how we can trust something that has
the ability to simulate emotions and make ethical decisions, but it does not inherently have these traits.
Human programming and use give it the impression that it has emotions and moral judgments (Imke &
Bas, 2021). “Robots exhibit AI as compared to humans. Human intelligence and animal intelligence both
display consciousness and emotions, whereas the other does not.” (Taherdoost & Madanchian, 2024)
Benefits of Artificial Intelligence
To start, AI might revolutionize many aspects of society for the better. As an example,
healthcare systems driven by AI have the potential to improve health outcomes through more accurate
and efficient illness diagnosis compared to humans (Willcocks, 2020). This coincides with the argument
put forward by those who believe in artificial intelligence is that it can increase productivity, expand
human capabilities, and even transform whole sectors. The article “How scientists are using artificial
intelligence: Al Science states “what to require a computer-science degree and lines of arcane
programming languages can now be done with user-friendly AI tools, often made to work after a query
to ChatGPT, OpenAI’s chatbot. Thus, scientists have easy access to what is essentially a dogged,
superhuman research assistant that will solve equations and tirelessly sift through enormous piles of
data to look for any patterns or correlations within.” (Global Business Review, 2023) Nevertheless, it is
crucial to thoroughly evaluate the dangers associated with these advantages.
Major concerns of AI
Problems include issues of data security and privacy as well as moral quandaries like job loss and
the equity of AI (Papagiannidis, Mikalef, Conboy, & Van De Wetering, 2023). The possibility of job loss as
a result of automation is a significant issue. Jobs that were once filled by humans may soon be filled by
AI as it gains more and more advanced capabilities (Hunt, Sarkar, Warhurst, 2022). Some see this as an
inevitable result of technological development, while others express concern about the societal and
economic fallout from widespread joblessness. Ensuring employees have the tools they need to adjust
to a dynamic labor market is crucial in reducing this risk. Concerns about how AI will affect the security
and confidentiality of data are another area of focus. The more AI permeates our life, the more personal
data it will be able to access. We need to know how this data will be utilized and safeguarded (Prox,
2023).The appropriate and transparent use of personal data, as well as the person's control over such
data, is super important.
It is critical to encourage individuals to work together, communicate, and educate themselves to
resolve these issues. Legislators, corporate businesspeople, higher education administrators, and
ordinary citizens all fall within this category. Participants may guarantee ethical and sustainable
development of AI by coordinating their efforts to weigh the potential advantages and hazards.
Collaboration
Since artificial intelligence (AI) is a complicated and diverse area that calls for feedback from a
wide range of those involved, collaboration is key. Various domain experts and affected community
leaders should work together in a collaborative approach to AI development, according to a proposed
plan (Roberts, Josh, Marley, Mariarosaria, Wang, & Luciano, 2021). “The main objective is to support
human workers rather than replace them.” (Passalacqua, Pellerin, Yahia, Magnani, Rosin, Joblot, &
Léger). Legislators and business moguls can collaborate on AI regulation frameworks that encourage
ethical research and development. For the advancement of artificial intelligence (AI) and its societal
benefits, academics and business moguls can work together. The community may also weigh in on how
AI should be shaped to meet their priorities and prompt further explanations of how AI systems make
judgments and the capacity to defend those decisions in the event of a dispute (Du, 2023).
Communication
Another reason communication is so important is that it allows all parties involved to better
comprehend one another's points of view and worries. Participants may learn where they agree and
disagree and then collaborate to discover solutions that work for everyone if they communicate
honestly and openly. For instance, business moguls may inform lawmakers of their AI development
goals so that rulebooks can be crafted to foster innovation while preserving personal information and
digital privacy.
Education
People need to be educated on the pros and cons of AI so they can make informed decisions
about how it will affect their life. People may make better choices about the development and usage of
AI if they are educated about it. For instance, for people to be ready for a changing work market,
lawmakers might inform the public on the effects of AI on the job market.
Finally, as we go forward with AI development, it is critical to promote public education of
Artificial Intelligence, communication, and collaboration while carefully weighing the potential
advantages and hazards of AI. If we all pitch in to make AI a positive force for good, we can make sure it
helps humans out, keeps their data safe, and does not lead to significant loss of jobs. Our continued
vigilance over AI research and development is critical so that we can adjust our policies to meet
emerging threats.
References
Andrews, M. (2023, Jun 01). Can we really put our trust in AI systems?: A growing number of
experts have said artificial intelligence development should be slowed or halted. So
should we be worried? Shropshire Star https://go.openathens.net/redirector/liberty.edu?
url=https://www.proquest.com/newspapers/can-we-really-put-our-trust-ai-systems/
docview/2821263835/se-2
Taherdoost, H., & Madanchian, M. (2024). AI Advancements: Comparison of Innovative
Techniques. Ai, 5(1), 38. https://doi.org/10.3390/ai5010003
Imke, v. H., & Bas, A. (2021). Viewpoint: AI as Author – Bridging the Gap Between Machine
Learning and Literary Theory. The Journal of Artificial Intelligence Research, 71, 175-
189. https://doi.org/10.1613/jair.1.12593
How scientists are using artificial intelligence: AI Science. (2023). Global Business Review,
https://go.openathens.net/redirector/liberty.edu?url=https://www.proquest.com/trade-
journals/how-scientists-are-using-artificial-intelligence/docview/2878667312/se-2
Passalacqua, M., Pellerin, R., Yahia, E., Magnani, F., Rosin, F., Joblot, L., & Léger, P. M.
(2024). Practice With Less AI Makes Perfect: Partially Automated AI During Training
Leads to Better Worker Motivation, Engagement, and Skill Acquisition. International
Journal of Human–Computer Interaction, 1–21.
https://doi.org/10.1080/10447318.2024.2319914
Roberts, H., Josh, C., Morley, J., Mariarosaria, T., Wang, V., & Luciano, F. (2021). The Chinese
approach to artificial intelligence: an analysis of policy, ethics, and regulation. AI &
Society, 36(1), 59-77. https://doi.org/10.1007/s00146-020-00992-2
Du M. (2023). Machine vs. human, who makes a better judgment on innovation? Take GPT-4
for example. Frontiers in artificial intelligence, 6, 1206516.
https://doi.org/10.3389/frai.2023.1206516
Willcocks, L. (2020). Robo-Apocalypse cancelled? Reframing the automation and future of work
debate. Journal of Information Technology, 35(4), 286–302.
https://doi.org/10.1177/0268396220925830
Papagiannidis, E., Mikalef, P., Conboy, K., & Van De Wetering, R. (2023). Uncovering the dark
side of AI-based decision-making: A case study in a B2B context. Industrial Marketing
Management, 115, 253–265. https://doi.org/10.1016/j.indmarman.2023.10.003
Hunt, W., Sarkar, S., & Warhurst, C. (2022). Measuring the impact of AI on jobs at the
organization level: Lessons from a survey of UK business leaders. Research Policy,
51(2), 104425. https://doi.org/10.1016/j.respol.2021.104425
Prox, R. (2023). DATA & INFRASTRUCTURE SECURITY: THE RISK OF AI ENABLED CYBER
ATTACKS AND QUANTUM HACKING. The Journal of Intelligence, Conflict, and
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