Authors

1. Dr. Minaxi Mittal

Affiliation

• Assistant Professor, Department of Commerce, S.A. Jain (P.G.) College, Ambala City

Abstract

At the vanguard of technological innovation, artificial intelligence (AI) is revolutionizing markets and changing the face of entrepreneurship by opening up new business opportunities, improving operational effectiveness and enabling previously unheard-of degrees of customisation for goods and services. Artificial intelligence (AI) driven technologies like automation, machine learning, natural language processing and predictive analytics are giving business owners the ability to innovate and grow quickly. Concerns regarding bias, accountability, transparency, privacy and wider societal effects have emerged as AI systems are included into decision-making processes, posing issues about how to strike a balance between innovation and moral obligation.
In AI ethics, accountability and transparency are equally important concerns. AI systems' decision-making processes are sometimes opaque, which makes it challenging to comprehend how and why particular judgments are made. This is a problem known as the "black box" issue. It could be challenging to assign blame for unanticipated or detrimental results that AI systems produce because of this lack of transparency. This implies that the application of AI complicates conventional ideas of accountability and liability for business owners.
Another major ethical challenge in AI entrepreneurship is privacy, especially as AI systems frequently need access to sensitive and personal data in enormous quantities. Important concerns concerning permission, data security and misuse potential are brought up by the use of such data. Entrepreneurs have to strike a compromise between upholding individual privacy rights and using data to fuel AI-driven innovation. This entails putting strong data security mechanisms in place, like encryption and anonymization, adhering to data privacy laws and promoting openness on data collecting and usage procedures.
Beyond personal ethical worries, AI has a significant and wide-ranging impact on society. AI's automation potential can boost productivity and economic expansion, but it also raises employment concerns because computers may eventually replace people in tasks that have historically been done by humans. The possibility of job displacement prompts more general inquiries concerning the nature of employment in the future and economic inequality. Entrepreneurs need to think about these societal ramifications and investigate ways to lessen any potential bad effects. Some of these strategies include funding programs for upskilling and reskilling, helping with workforce transitions and interacting with legislators to create inclusive AI policies that take into account the needs of various communities.
This study attempts to give a thorough analysis of the ethical problems that arise in AI entrepreneurship, looking at the roles that AI entrepreneurs should play in resolving these problems and offering solutions for striking a balance between innovation and responsibility. This paper aims to provide a road map for responsible AI development by examining current ethical frameworks, examining case studies and talking about recommended practices. It highlights the significance of incorporating ethical considerations into the AI lifecycle at every level from design and development to deployment and monitoring and it promotes an ethically conscious organizational culture.

Keywords

AI Ethics, AI Entrepreneurship, Innovation, Responsibility, Techno ethics

References

1. Whittlestone, J., Nyrup, R., Alexandrova, A., & Dinsmore, T. (2019). AI ethics: The importance of a multi-disciplinary approach. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society.
2. Russell, S., & Norvig, P. (2020). Artificial intelligence: A modern approach (4th ed.). Pearson Education.
3. Jobin, A., Ienca, M., & Andorno, R. (2019). Artificial intelligence: The global landscape of ethics guidelines. AI & Society, 34(4), 685-704. https://doi.org/10.1007/s00146-019-00880-1
4. Dignum, V. (2019). Responsible artificial intelligence: Designing AI for human values. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society.
5. Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. In Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency.
6. Zarsky, T. (2016). Privacy, technology, and the future of work. Harvard Law Review, 129(6), 1441-1493. https://harvardlawreview.org/2016/04/privacy-technology-and-the-future-of-work/