Short Communication, J Comput Eng Inf Technol Vol: 12 Issue: 4

Privacy and Data Protection in the Age of AI and Robotics

Yu Chen^*

¹Department of Computer Science, University of Chinese Academy of Sciences, Beijing, China

*Corresponding Author: Yu Chen,
Department of Computer Science, University of Chinese Academy of Sciences, Beijing, China
E-mail: yu.chen@cas.edu.cn

Received date: 28 June, 2023, Manuscript No. JCEIT-23-112367

Editor assigned date: 30 June, 2023, Pre QC No. JCEIT-23-112367 (PQ);

Reviewed date: 14 July, 2023, QC No. JCEIT-23-112367

Revised date: 24 July, 2023, Manuscript No. JCEIT-23-112367 (R);

Published date: 31 July, 2023, DOI: 10.4172/2329-955X.1000285

Citation: Chen Y (2023) Privacy and Data Protection in the Age of AI and Robotics. J Comput Eng Inf Technol 12:4.

Description

Ethical considerations in the fields of Artificial Intelligence (AI) and robotics have gained significant attention as these technologies advance and become more integrated into various aspects of society. The rapid development and deployment of AI and robotics raise complex ethical questions that encompass issues of fairness, accountability, transparency, privacy, bias, and the potential societal impact [1]. This study discuss into the key ethical considerations in AI and robotics, highlighting the challenges and potential solutions to navigate the ethical landscape of these transformative technologies [2].

One of the fundamental ethical concerns in AI and robotics is fairness. AI systems and robots are trained on vast datasets, and if these datasets contain biases, the technology can perpetuate those biases in decision-making processes [3]. For instance, biased algorithms could lead to discriminatory outcomes in areas like hiring, lending, and criminal justice. Ensuring fairness requires careful scrutiny of training data, continuous monitoring, and the implementation of algorithms that are sensitive to underrepresented groups [4].

AI and robotics often involve complex algorithms and decisionmaking processes that can be difficult to understand for nonexperts. The lack of transparency can lead to a lack of accountability when things go wrong [5]. To address this, developers and organizations need to ensure transparency in their systems, making it clear how decisions are made and enabling external audits. This transparency also helps build trust between technology providers and users. AI and robotics rely heavily on data collection and analysis. However, the massive amounts of data collected raise concerns about privacy and data protection [6].

Ethical considerations demand that personal data be handled responsibly and in accordance with relevant regulations. Anonymization and data minimization techniques are essential to mitigate risks of unauthorized access or misuse of sensitive information [7]. As robots become more autonomous, the question of who is responsible for their actions becomes dire. If a self-driving car is involved in an accident, is the manufacturer, the owner, or the AI responsible? Establishing clear lines of responsibility and legal frameworks for autonomous systems is a complex ethical challenge [8].

AI and robotics have the potential to automate tasks and jobs traditionally performed by humans. While this can increase efficiency, it can also lead to job displacement and economic inequalities. Ethical considerations involve understanding the potential impact on the workforce and creating strategies to reskill and transition affected workers to new roles. AI and robotic systems can be vulnerable to hacking and manipulation, leading to potentially disastrous consequences. Ensuring the security of these systems is not only an ethical obligation but also a matter of public safety. Developers must prioritize cybersecurity and implement robust measures to prevent unauthorized access and malicious use [9]. The development of lethal autonomous weapons, also known as killer robots, raises profound ethical concerns. These weapons can make decisions about who to target and when to attack without human intervention. The deployment of such weapons could lead to loss of human control and the erosion of ethical principles in warfare. To address these ethical considerations, the development and deployment of AI and robotics require clear ethical frameworks and regulations [10]. Governments, international organizations, and industry stakeholders are working on guidelines to ensure that AI and robotic technologies are developed and used in ways that prioritize human values and rights.

Conclusion

The ethical considerations in AI and robotics are complex and multifaceted, touching on issues of fairness, transparency, accountability, privacy, autonomy, and societal impact. As these technologies continue to evolve and become more integrated into the lives, it is imperative to proactively address these ethical challenges. Collaboration between technology developers, policymakers, ethicists, and society at large is essential to ensure that AI and robotics contribute to the betterment of humanity while respecting fundamental ethical principles. By navigating these considerations thoughtfully and responsibly, all can harness the potential of AI and robotics for the benefit of all.

References

1. Ekman P, Raggio RD (2016) Thompson, S.M. Service Network Value Co-Creation: Defining the Roles of the Generic Actor. Ind Mark Manag 56: 51–62.

   [Google Scholar] [CrossRef]

2. Bargal D, Gold M, Lewin M (1992) Introduction: The heritage of kurt lewin. J Soc Issues 48: 3–13.

   [Google Scholar] [CrossRef]

3. Galli BJ (2018) Change management models: A comparative analysis and concerns. IEEE Eng Manag Rev 46(3): 124–132.

   [Google Scholar] [CrossRef]

4. Nam EJ, Kim SW, Lee M, Yim GW, Paek JH et al. (2011) Robotic single-port transumbilical total hysterectomy: A pilot study. J Gynecol Oncol 22: 120–126.

   [Google Scholar] [CrossRef]

5. Lee DH, Nam SH, Song T, Kim WY, Lee KW et al (2015) Public perception of ‘scarless’ laparoendoscopic single-site surgery in gynecology. Obstet Gynecol Sci 58: 289.

   [Google Scholar] [CrossRef]

6. Akkaş MA, Sokullu R (2017) An IoT-based greenhouse monitoring system with Micaz motes. Procedia Comput Sci 113: 603-608.

   [Google Scholar]

7. Maksimović M (2018) Implementation of fog computing in IoT-based healthcare system. J Inf Technol 14: 100-107.

   [Google Scholar]

8. Chris L, Brigo D, Hoy D (2017) Impact of Robotics, RPA and AI on the insurance industry: challenges and opportunities. Journal of Financial Perspectives. J Econ Perspect 4(1): 556-564.

   [Google Scholar]

9. Yusof YM, Islam AM, Baharun S (2015) An experimental study of WSN transmission power optimisation using MICAzmotes. ICAEE 182-185.

   [Google Scholar]

10. Rupali S, Hemant G, Shoaib K, Aaditya I, Deep D (2018) IOT based greenhouse monitoringsystem. Int J Appl Sci Eng 6:2084-2085.

    [Google Scholar]