ETHICAL IMPLICATIONS OF AI-DRIVEN STRATEGY
FORMULATION
This section provides an overview of the ethical challenges and
considerations tied to AI’s growing role in strategic business
formulation, drawing from key academic papers to illustrate each point.
The Nature and Origin of Biases in AI
Algorithms
AI algorithms can acquire biases from human-generated data, often
reflecting historical prejudices. Buolamwini & Gebru (2018) [7]
highlighted the biases in facial recognition technologies, especially in
gender classification based on skin type. This example shows how biases
in training data can lead to skewed AI decisions.
Ethical Dilemmas Stemming from AI
Decision-making
With AI’s role in critical decision-making, ethical challenges such as
fairness in algorithmic decisions arise. Rahwan et al. (2019) [26]
explored the complex moral dilemmas associated with machine morality.
Issues of accountability in AI errors, like those in AI-driven vehicles,
call for transparent and explainable AI systems.
Regulatory Challenges and
Proposals
The fast pace of AI development poses challenges for regulatory
frameworks. Brundage et al. (2018) [4] discussed the implications of
malicious AI use and proposed comprehensive policy responses.
Regulations like GDPR aim to control AI usage by giving individuals more
data control.
Industry’s Responses to AI Ethical
Concerns
Industries are responding to these ethical issues by forming ”Ethical
AI” divisions and creating guidelines for AI fairness and transparency.
Google’s ”AI Principles” set standards for responsible AI development
and use. The partnership on AI, including major tech companies (Russell,
Dewey, & Tegmark, 2015) [28], focuses on sharing best practices for
ethical AI implementation, recognizing the need to balance AI benefits
with ethical considerations.
This overview highlights that while AI offers significant advantages in
strategic business formulation, it also raises important ethical issues
that need careful consideration and action from both industries and
regulatory bodies.
TABLE 6: ETHICAL IMPLICATIONS OF AI-DRIVEN STRATEGY FORMULATION