Benchmark - Technology, Diversity, and Ethics

1 Benchmark - Technology, Diversity, and Ethics It is important for leaders to understand how digital technology affects leadership and its role in shaping organizational culture, diversity, performance, and work processes as businesses continue to embrace a more collaborative style. People have different perceptions of ethics. What one culture holds as ethical may not be the same with another culture. Therefore, Johnson (2015) points out that leaders must understand how to make ethical decisions in diverse groups. Thus, this essay discusses the potential ethical issues leaders may encounter in managing technology and diversity in an organization and the strategies the leaders may use to mitigate potential ethical issues resulting from technology and diversity.

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2 Potential Ethical Issues Leaders may Encounter in Managing Technology and Diversity in a Firm Digital technologies significantly influence work and change in companies across the globe. Despite being a transforming solution to problems, it is sometimes difficult to predict technology when it comes to such issues as performance, organizational culture, and work.

Artificial intelligence is one of the forms of technology that have been adopted by multinational organizations such as Google, Netflix, and Amazon Inc. This form of technology has greatly changed how such companies function. According to Haenlein and Kaplan (2019), artificial intelligence refers to the ability of a system to unravel external data correctly, learn from it, and make sense of such understanding to accomplish specific goals and tasks through flexible adaptation. Haenlein and Kaplan (2019) further describe artificial intelligence as an advanced algorithm efficient in ensuring increased productivity by utilizing computers and data for progressively complex tasks in a faster and cheaper manner than individuals or human beings.

However, the issues of algorithm bias have resulted in a lot of concerns when it comes to artificial intelligence. According to Townes-Whitley (2017), algorithm bias is an ethical concern when it comes to the development of most technologies. Bias is evidenced in automated facial recognition and the associate data sets, leading to reduced accuracy in recognizing darkerskinned individuals, especially ladies. The use of artificial intelligence in the healthcare sector has also resulted in some concerns. For instance, it is a requirement for machine learning datasets to be large and often used in clinical trial research databases, which are generally acquired from majority populations. Thus, the chances of the algorithms failing when used in underserved or underrepresented patient groups are very high.

3 Another issue with the use of artificial intelligence in business concerns automation bias.

Automation bias can possibly reduce the probability of healthcare providers questioning an inaccurate result because of the increased reliance on automated systems. Such systems have been developed to improve patient safety and minimize human error. However, a study carried out by Safdar, Banja, and Meltzer (2020) shows how malware and artificial intelligence deep learning tools can potentially misinform expert radiologists on the existence or non-existence of malignant lung lesions on CT scans.

How Leaders can Mitigate Potential Ethical Issues Resulting from Technology and Diversity One of the primary issues faced by businesses across the globe is having the right leadership talent to secure such key competencies as systems integration, user-interface development, software application engineering, and data scientist skills to translate data meaning into strategic actions. Further, Migliore and Chinta (2017) point out that workplace productivity has also been adversely affected in most firms primarily because of inadequate digital skills.

Companies should also put in place the right organizational structure that makes it easier to adopt digital technologies. The chances are that organizational structures will potentially become less inflexible as organizational members get to acknowledge more effective collaboration opportunities. Managers will be in a position to monitor and mentor a greater number of their subordinates because of the increased span of control facilitated by the transparency of knowledge work (Schildt, 2016).

With regards to the mitigation of ethical issues resulting from technology and diversity issues, many businesses have understood and are working round the clock to close the cultural gaps through the incorporation of functions that solely focus on diversity and inclusion.

4 Successful companies have introduced diversity and inclusion training in which organizational members are trained to cultivate more diverse and all-inclusive firms. Such training is instrumental in addressing unintentional bias and promoting effective decision-making, team collaboration, and management. The training can help identify and manage unintentional bias in career development, team dynamics, and recruitment and hiring of the employees. The training also offers workshops on growth mindset in which employees are taken through the drawbacks of fixed and growth mindsets, how to develop a growth mindset, and how to institutionalize into the company's culture. Support from the top management is critical to ensuring the success of such training (Johnson, 2019).

Conclusion In summary, people have varying perceptions of ethics. What one culture holds as ethical may not be the same with another culture. Therefore, leaders must understand how to make ethical decisions in diverse groups. Digital technologies significantly influence work and change in companies across the globe. Despite being a transforming solution to problems, it is sometimes difficult to predict technology when it comes to such issues as performance, organizational culture, and work. Artificial intelligence has greatly changed how such companies function. Artificial intelligence refers to the ability of a system to unravel external data correctly, learn from it, and make sense of such understanding to accomplish specific goals and tasks through flexible adaptation. It is an advanced algorithm efficient in ensuring increased productivity through the utilization of computers and data for progressively complex tasks in a faster and cheaper manner than individuals or human beings. However, the issues of algorithm bias have resulted in a lot of concerns when it comes to its use. Leadership styles result from an individual's authentic self and are based on core values and beliefs. For successful workflow,

5 organizations need to have leaders who can mitigate any potential ethical technology and diversity. This can be achieved by implementing diversity and inclusion training to address unintentional bias and growth mindset. Such training is instrumental in promoting effective decision-making, team collaboration, as well as easy management. The training can help identify and eradicate any unethical practices in career development, team dynamics, and recruitment and hiring of the employees. On the other hand, workshops on growth mindset can also be organized in which the organizational leaders are trained on the drawbacks of fixed and growth mindsets, how to develop a growth mindset, and how to institutionalize it into the company's culture.

6 References Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5-14.

Johnson, C. E. (2019). Meeting the ethical challenges of leadership: Casting light or shadow.

Sage Publications.

Migliore, L. A., & Chinta, R. (2017). Demystifying the Big Data Phenomenon for Strategic Leadership. SAM Advanced Management Journal, 82(1).

Safdar, N. M., Banja, J. D., & Meltzer, C. C. (2020). Ethical considerations in artificial intelligence. European Journal of Radiology, 122, 108768.

Schildt, H. (2017). Big data and organizational design–the brave new world of algorithmic management and computer augmented transparency. Innovation, 19(1), 23-30.

Townes-Whitley, T. (2017, June 7). Ethics in emerging technologies [Video]. https://ecorner.stanford.edu/in-brief/ethics-in-emerging-technologies/