This study tries to answer these questions and investigates the ethical challenges of ADM (Algorithm Decision Making) arisen in the context of ethical decision-making and their ethical outcomes.
Algorithms and algorithmic decision-making simplify and improve people's lives and create new values for our society. ADM is used by banks to establish creditworthiness or by the police to calculate the likelihood of future crimes. It is used in agriculture, aviation, the insurance industry, and many other business areas. ADM is becoming increasingly essential and plays a crucial role in our daily life.
However, the use of algorithms is not just about opportunities and benefits. ADM hides significant risks and creates further ethical challenges. The ethics of algorithms is a provocative topic that causes a lot of controversies. As well as the application of ADM in the ethical context. Is it ethical to use algorithmic decision-making? Is the decision-maker "moral aware" of applying ADM?. Does moral awareness about the ethical implications of ADM always lead to ethical decisions?
Table of Contents
- Introduction
- Algorithmic decision making
- Algorithmic selection & algorithmic decision making
- Use of algorithmic decision making and their risks
- Algorithmic decision making, ethical challenges and outcomes in the context of ethical decision making
- Moral awareness and ethical challenges of ADM
- Moral decision making and ethical outcomes
- Amoral decision making and ethical outcomes
- Conclusion
Objectives and Key Themes
This study investigates the ethical challenges of algorithmic decision making (ADM) in the context of ethical decision making, focusing on the ethical outcomes arising from its application. The research draws heavily on the Model of Tenbrunsel and Smith-Crowe, examining how moral awareness, moral decision making, and amoral decision making processes influence ethical outcomes when ADM is employed.
- Ethical challenges and outcomes of algorithmic decision making
- Moral awareness in the context of ADM
- Influence of moral and amoral decision making on ethical outcomes
- The role of ADM in various life areas
- Risks associated with the implementation of ADM
Chapter Summaries
- Introduction: This chapter introduces the concept of algorithms and algorithmic decision making (ADM), highlighting its growing importance and impact on various life aspects. It also acknowledges the potential risks and ethical challenges associated with ADM, setting the stage for further exploration.
- Algorithmic decision making: This section provides a deeper understanding of ADM by exploring its key components, including algorithmic selection. It delves into the various applications of ADM across diverse fields and emphasizes the inherent risks associated with its implementation.
- Algorithmic decision making, ethical challenges and outcomes in the context of ethical decision making: This chapter examines the ethical challenges of ADM in the context of ethical decision making. It explores the concept of moral awareness and its relevance to ADM, and analyzes how moral and amoral decision making processes can lead to different ethical outcomes when ADM is involved.
Keywords
This study explores the ethical implications of algorithmic decision making (ADM), focusing on moral awareness, ethical challenges, and outcomes. The study examines various areas of ADM application, highlighting the risks involved, and analyzes how moral and amoral decision-making processes influence ethical outcomes in the context of ADM. Key concepts explored include ethical decision making, algorithmic selection, and the impact of ADM on society.
Frequently Asked Questions
What is Algorithmic Decision-Making (ADM)?
ADM refers to the use of algorithms and data to make or assist in making decisions that affect individuals or society, such as credit scoring or risk assessment in policing.
What are the main ethical challenges of ADM?
Key challenges include bias in data, lack of transparency (black box effect), accountability issues, and the potential for unfair discrimination against certain groups.
What is "moral awareness" in the context of algorithms?
Moral awareness is the recognition that an algorithmic decision has ethical implications. It is a crucial step for developers and users to ensure that ADM leads to ethical outcomes.
Can an algorithm make a "moral" decision?
Algorithms themselves are not moral agents; however, the study analyzes how the moral or amoral decision-making processes of the people who design and deploy them shape the final outcomes.
In which areas is ADM commonly used today?
ADM is widely used in banking (creditworthiness), insurance, law enforcement (predictive policing), agriculture, and aviation.
What are the risks of implementing ADM in society?
Risks include the erosion of privacy, the reinforcement of societal inequalities through biased data, and a decrease in human oversight over critical life-altering decisions.
- Citar trabajo
- Anastasia Kabushka (Autor), 2019, Ethics of Algorithms. Ethical Challenges and Outcomes of Algorithmic Decision-Making, Múnich, GRIN Verlag, https://www.grin.com/document/1031107
