Unethical Uses of AI

PART A

Various industries and sectors fear that there are a significant number of cases of unethical uses of AI in real-world scenarios. Ethical dilemmas are faced by the individuals and entities that design, use, and deploy AI solutions (Tsamados et al., 2021). Inclusive in this context are the occurrence of biased algorithms which amplify discrimination, digital technology invasion, and opaque automated decisions that raise an issue of ethical implementation of AI (Tsamados et al., 2021). These issues occur in sectors such as healthcare, finance, the criminal justice system and social media platforms. Since AI has been incorporated into various everyday functions and decision-making processes, providing solutions to AI raised concern is an immediate concern (Rendtorff and Mattson, 2009). Profitable motivation, absence of regulation or prejudices from multiple backgrounds also create the issue and should be considered. Thus, transparency must be guaranteed in AI systems development and application while sticking to ethics to restrict AI-related risks and assure people’s trust since AI is rapidly developing.

PART B

Analyzing the external factors of OpenAI brings up an array of significant challenges. Regulation structures like GDPR limit handling, which affects the production of OpenAI products or services. The case of GDPR highlights the need for strict privacy measures, which, when implemented, affect the company’s data-driven research and development projects (Rintamaki, 2023). From an economic perspective, AI assimilation improves the economy’s performance but also contributes to job losses and economic inequalities (Ani, 2024). To illustrate, various manufacturing sectors have laid off workers with the aim of automating production. Socially, consumer preferences are influenced by changing demographics and cultural barriers towards AI technologies. For instance, Japan has an increasing number of the elderly than ever before leading to demand for elderly care robots hence requiring specific societal oriented AI solutions (Lee, Kwak and Song, 2020). Technologically, the government’s preference and encouragement policy influences consumer acceptance of the innovation. In Canada, for instance, grants offered by the government bring about the push for technological developments in the country, hence allowing for further research on AI (Nmirabal, 2023. The environmental impact of artificial intelligence also includes the unsustainable power usage by the AI or its carbonation of the atmosphere (Gaur et al., 2023). Data centres utilize lots of energy to ensure proficient operations, contributing to environmental pollution. Ideally, legal compliance with laws that shield consumers from discrimination is critical (Gaur et al., 2023). An example of this law is the Civil Rights Act, which ensures a fair recruitment process for employees and protects user privacy rights.

PART C

Data Privacy Concerns

OpenAI finds it a daunting task to navigate through regulatory frameworks such as GDPR, which impose strict regulations on the handling of data. Conformity to the procedures is essential for the research and developmental activities of the company because violation leads to legal issues, and, through it, the company’s reputation is damaged (Dhirani et al., 2023). Data privacy concerns are not just about complying with the law but also an ethical matter recognizing individual’s data as private and essential to their autonomy (Dhirani et al., 2023). Consequently, compromising data privacy can harm user trust and impact the organization’s operational efficiencies or performance. Besides, according to Auxier et al. (2019), 79% of Americans are concerned about how companies use their data, demonstrating the significance of dealing with data privacy. By doing so, the company can ensure public confidence and trust. This is significantly expressed in the Cambridge Analytica scandal, which showed the repercussions of mishandling user data (Arora and Zinolabedini, 2019).

OpenAI should take data privacy concerns seriously. Deficiency of this can dent its reputation and credibility and hinder future prosperity. Ideally, it should adopt Goal 16 of the United Nations Sustainable Development Goals (UNSDGs), a framework that necessitates adherence to consumer rights to privacy and access to information (Stallings, 2020). Failure to comply with data privacy terms may lead the company to legal turmoil, tarnishing its image and losing the trust of its several users. To maintain good relations with users and stakeholders, as the above, Open AI must strictly comply with GDPR as it implies transparency and integrity.

OpenAI should be concerned with data privacy, as it can have severe ethical and legal implications. OpenAI can apply the deontological ethical approach to emphasize moral principles and obligations independent of consequences (Frémeaux, Donato, and Noël-Lemaitre, 2023). This framework implies that respecting an individual’s privacy is just an example which reflects the fundamental moral responsibility concerning personal autonomy and self-esteem (Frémeaux, Donato, and Noël-Lemaitre, 2023). Hence, implementing GDPR-compliant data protection measures by OpenAI shows compliance with ethical norms. Otherwise, the violation of confidentiality might lead to mistrust of the user’s confidence and legal accusations.

Environmental impact concern

Another issue OpenAI must address is the environmental implications of the amount of energy their artificial intelligence operations consume and generation of CO2 emissions Gaur et al., 2023). It should be noted that data centers are the engines behind artificial intelligence (AI) systems, known for their heavy use of power. According to Thangam et al. (2024), 3% of the worlds electricity usage is being led by data centers, portraying how AI technologies influence the environment. Additionally, increased AI applications all over point to increased energy usage in the coming years (Thangam et al., 2024). Hence, given its position as a leading company in the AI industry, OpenAI should adopt methods which conserve energy and therefore decrease their carbon footprint as a way of supporting global efforts to preserve our environment and make it sustainable in future.

OpenAI must advocate for an environmental accountability audit in that it has a direct link with all human activities that will significantly impact the environment’s well-being and Earth’s sustainability (Jia et al., 2024). Failure to address this issue could cause things to escalate into catastrophic consequences such as increasing global warming, environmental decline, and disruption of ecosystems. From a utilitarian perspective, it is necessary to prioritize sustainability initiatives that would benefit most people today and in future times (Jia et al., 2024). In other words, Utilitarianism weighs the overall consequences for a group or society as it tries to achieve the greatest good for maximum number of individuals (Brokerhof et al., 2023). This way, OpenAI can focus on actions that contribute most effectively to society by reducing its carbon footprint, saving energy and combating climate change (Brokerhof et al., 2023).

OpenAI should be seriously alarmed by the fact that it contributes to environmental degradation. In order to stress how urgent it is for humanity to tackle climate change, OpenAI must conform with United Nations’ Sustainable Development Goals (UNSDGs), especially Goal 13- Climate Action (Sandberg, 2023). As per Goal 13, carbon emissions reduction and energy efficiency improvement play a critical role in ensuring that climate changes are mitigated while also preventing their adverse effects. For instance, IPCC reports note that the need for a radical reduction of CO2 emissions is fundamental to maintaining global warming below levels of 1.5 degrees (Popkova and Shi, 2022).

PART D: Recommendations

OpenAI should highly value information protection that exceeds regulatory compliance in a bid to quell the worries that have been raised about data privacy. These measures would improve encryption protocols and implement strict access controls. Another plausible option can be for OpenAI to invest directly in continuous education and attention programs that foster an environment for data confidentiality and protection across all fronts (Sandberg, 2023).

Besides, OpenAI is responsible for prioritizing sustainability solutions based on the management of its activities. This, in simple terms, means a reliance on sources of energy that eliminate the polluting effect on the environment (Brokerhof et al., 2023). However, such a scheme is inevitably accompanied by the financial side effect of the large sums necessary for faculty upgrades, equipment acquisition, and the adoption of technology required (Brokerhof et al., 2023). In this case, OpenAI may exploit green bonds as one option or collaborate with top environmental organizations during their fundraising processes to reduce the risk factor involved when they plough in their capital investments for such projects. In addition, keeping partners involved, exploring all possibilities with them, and being transparent about all actions is crucial.

PART E

Studying these sections has provided me with significant inputs on the background of AI development, especially OpenAI. Part A talked about the challenging ethical scenarios one faces, like privacy issues. I realized through this analysis that precautionary measures had to be taken in the protection of data privacy. A number of things became clearer for me after using the PESTEL framework in Part B, which helped me analyze the external environment of OpenAI and created awareness on various issues like compliance or technological innovations. Additionally, Part C delved into more ethical and developmental questions about topics such as data privacy and environmental impact. At that point exactly, I finally knew about the significance of trust and accountability extension from OpenAI up to users. I also learnt that different ethical frameworks such as deontologist and utilitarianism are very essential in developing ethical practices within an organization. I have also learnt that ethical frameworks enable companies and individuals make ethical decisions.

In essence, certain proposals must be made to address these concerns henceforth focusing on data protection. Also learned how to go beyond one’s comfort zone by asking complex ethical and environmental questions that are usually hard to resolve. Finally, a general examination at this level has bestowed upon me with an understanding of how business strategies can be ethically developed but still meet sustainability within the complexity surrounding AI. However much my decision-making process has retained its status quo for most cases though not all are same. Now just more than ever before I do understand how multifarious moral problems in this regard should have caring AI leaders who care for us responsibly conserve nature when thinking about artificial intelligence advancement.

References

ANI 2024. 40% of global employment could be disrupted by Artificial Intelligence: IMF. [online] @bsindia. Available at: https://www.business-standard.com/world-news/40-of-global-employment-could-be-disrupted-by-artificial-intelligence-imf-124011500859_1.html [Accessed 21 Mar. 2024].

Arora, N. and Zinolabedini, D. (2019). The Ethical Implications of the 2018 Facebook-Cambridge Analytica Data Scandal. repositories.lib.utexas.edu. [online] doi:https://doi.org/10.26153/tsw/7590.

Auxier, B., Rainie, L., Anderson, M., Perrin, A., Kumar, M. and Turner, E. 2019. Americans and privacy: Concerned, confused and feeling lack of control over their personal information. [online] Pew Research Center. Available at: https://www.pewresearch.org/internet/2019/11/15/americans-and-privacy-concerned-confused-and-feeling-lack-of-control-over-their-personal-information/.

Bailey, M.J., Helgerman, T.E. and Stuart, B.A., 2023. How the 1963 Equal Pay Act and 1964 Civil Rights Act Shaped the Gender Gap in Pay (No. w31332). National Bureau of Economic Research.

Brokerhof, I.M., Sucher, S.J., Matthijs Bal, P., Hakemulder, F., Jansen, P.G. and Solinger, O.N., 2023. Developing moral muscle in a literature-based business ethics course. Academy of Management Learning & Education, 22(1), pp.63-87.

Dhirani, L.L., Mukhtiar, N., Chowdhry, B.S. and Newe, T., 2023. Ethical dilemmas and privacy issues in emerging technologies: a review. Sensors, 23(3), p.1151.

Edmond, C. and North, M. 2023. More than 1 in 10 people in Japan are aged 80 or over. Here’s how its ageing population is reshaping the country. [online] World Economic Forum. Available at: https://www.weforum.org/agenda/2023/09/elderly-oldest-population-world-japan/.

Frémeaux, S., Donato, M. and Noël-Lemaitre, C., 2023. Virtuous Exemplarity in Business Ethics Education: Insights From the Platonic Tradition. Academy of Management Learning & Education, 22(3), pp.531-548.

Gaur, L., Afaq, A., Arora, G.K. and Khan, N., 2023. Artificial intelligence for carbon emissions using system of systems theory. Ecological Informatics, p.102165.

Ghanayem, A., Downing, G. and Sawalha, M., 2023. The impact of political instability on inflation volatility: The case of the Middle East and North Africa region. Cogent Economics & Finance, 11(1), p.2213016.

Harborth, D. and Pape, S. (2019). How Privacy Concerns and Trust and Risk Beliefs Influence Users’ Intentions to Use Privacy-Enhancing Technologies – The Case of Tor. Proceedings of the … Annual Hawaii International Conference on System Sciences. doi:https://doi.org/10.24251/hicss.2019.585

Jia, N., Luo, X., Fang, Z. and Liao, C., 2024. When and how artificial intelligence augments employee creativity. Academy of Management Journal, 67(1), pp.5-32.

Ke, T.T. and Sudhir, K. (2022). Privacy Rights and Data Security: GDPR and Personal Data Markets. Management Science, 69(8). doi:https://doi.org/10.1287/mnsc.2022.4614.

Lee, J.-W., Kwak, D.W. and Song, E. (2020). Aging Labor, ICT Capital, and Productivity in Japan and Korea. SSRN Electronic Journal. Doi:https://doi.org/10.2139/ssrn.3518875.

Myers, J. 2022. These will be the world’s most populous countries by 2030. [online] World Economic Forum. Available at: https://www.weforum.org/agenda/2022/08/world-population-countries-india-china-2030/.

Nmirabal 2023. Government Funding Programs Available to Support Innovation. [online] Canada. Available at: https://leyton.com/ca/insights/articles/government-funding-programs-available-to-support-innovation/#:~:text=The%20Canadian%20government%20offers%20several [Accessed 21 Mar. 2024].

Popkova, E.G. and Shi, X. (2022). Economics of Climate Change: Global Trends, Country Specifics and Digital Perspectives of Climate Action. Frontiers in Environmental Economics, 1. doi:https://doi.org/10.3389/frevc.2022.935368.

PWC 2018. PwC’s Global Artificial Intelligence Study: Sizing the prize. [online] PwC. Available at: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html.

Rajest, S.S., Singh, B., Obaid, A.J., Regin, R. and Chinnusamy, K. eds., 2023. Advances in artificial and human intelligence in the modern era. IGI Global.

Rendtorff, J.D. and Mattsson, J., 2009. Ethical issues in the service industries. The Service Industries Journal, 29(1), pp.1-7.

RINTAMÄKI, T.K., 2023. GDPR’s reflection in privacy-enhancing technologies: implications for AI data protection (Doctoral dissertation, European University Institute).

Sandberg, K.D., 2023. Open Source for Sustainability.

Stallings, W. (2020). Handling of Personal Information and Deidentified, Aggregated, and Pseudonymized Information Under the California Consumer Privacy Act. IEEE Security & Privacy, 18(1), pp.61–64. doi:https://doi.org/10.1109/msec.2019.2953324.

Thangam, D., Muniraju, H., Ramesh, R., Narasimhaiah, R., Khan, N.M.A., Booshan, S., Booshan, B., Manickam, T. and Ganesh, R.S., 2024. Impact of Data Centers on Power Consumption, Climate Change, and Sustainability. In Computational Intelligence for Green Cloud Computing and Digital Waste Management (pp. 60-83). IGI Global.

Tsamados, A., Aggarwal, N., Cowls, J., Morley, J., Roberts, H., Taddeo, M. and Floridi, L., 2021. The ethics of algorithms: key problems and solutions. Ethics, governance, and policies in artificial intelligence, pp.97-123.

Zhou, J. and Wang, M., 2023. The role of government-industry-academia partnership in business incubation: Evidence from new R&D institutions in China. Technology in Society, 72, p.102194.