Intro to Business Analytics

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Deontological ethics

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Intro to Business Analytics

Definition

Deontological ethics is an ethical theory that emphasizes the importance of duty and rules in moral decision-making, asserting that actions are morally right or wrong based on their adherence to a set of principles, regardless of the consequences. This perspective prioritizes the intention behind actions and adherence to moral duties, making it particularly relevant in discussions surrounding responsible decision-making in artificial intelligence and analytics.

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5 Must Know Facts For Your Next Test

  1. Deontological ethics is often associated with philosopher Immanuel Kant, who argued that moral obligations arise from rationality and universal laws.
  2. In the context of AI and analytics, deontological ethics stresses the need for algorithms to operate within established ethical guidelines, regardless of potential benefits.
  3. Deontologists often advocate for transparency in AI systems to ensure adherence to ethical principles and protect user rights.
  4. This ethical framework contrasts sharply with utilitarianism, which focuses on maximizing overall happiness and may justify harmful actions if they lead to greater good.
  5. Deontological ethics promotes the idea that certain duties, such as honesty and fairness, should not be compromised, even when faced with favorable outcomes from breaking them.

Review Questions

  • How does deontological ethics influence decision-making in artificial intelligence development?
    • Deontological ethics influences decision-making in AI development by emphasizing the importance of adhering to established moral duties and guidelines throughout the design and implementation processes. This means that developers must prioritize ethical standards such as fairness, transparency, and respect for user privacy, regardless of the potential benefits that may arise from bending these rules. In this way, deontological ethics ensures that technology aligns with societal values and protects individuals from harm.
  • Compare deontological ethics with consequentialism in the context of analytics. What are the key differences in how each approach addresses ethical dilemmas?
    • Deontological ethics focuses on the morality of actions based on adherence to rules and duties, while consequentialism assesses actions solely by their outcomes. In analytics, a deontologist would prioritize compliance with data privacy laws and ethical guidelines when processing information, viewing these obligations as non-negotiable. In contrast, a consequentialist might argue that if violating those rules leads to significant benefits—like improved public health—then it could be justified. This fundamental difference highlights the tension between adhering to moral principles versus pursuing perceived greater good.
  • Evaluate the role of deontological ethics in shaping public trust in AI technologies. How does this ethical approach contribute to societal perceptions?
    • Deontological ethics plays a critical role in shaping public trust in AI technologies by reinforcing the need for strict adherence to ethical standards and principles during their development and deployment. By ensuring that AI systems operate transparently and respect individual rights, developers can foster a sense of security among users who may be wary of how their data is handled. This commitment to moral duty not only builds credibility but also helps mitigate fears regarding privacy violations or discriminatory practices, ultimately contributing to more positive societal perceptions of emerging technologies.

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