Machine ethics: The robot’s dilemma

Deng, Boer

doi:10.1038/523024a

Cited by 77 publications

(40 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The enormous future potential of machine learning specifically, and artificial intelligence generally, requires to take not only over social responsibility, but even maximising the social benefit of these technologies [112]. Here it is important not only to take care of ethics in the sense of how humans use computational approaches, instead to deal with machine learning ethics, which is concerning the ethical dimension to ensuring that the behavior of machines toward human users is ethically acceptable [113], which is of increasing importance in learning machines, autonomous systems and decision making [114][115][116].…”

Section: Machine Learning Educationmentioning

confidence: 99%

Introduction to MAchine Learning & Knowledge Extraction (MAKE)

Holzinger¹

2017

MAKE

View full text Add to dashboard Cite

Abstract:The grand goal of Machine Learning is to develop software which can learn from previous experience-similar to how we humans do. Ultimately, to reach a level of usable intelligence, we need (1) to learn from prior data, (2) to extract knowledge, (3) to generalize-i.e., guessing where probability function mass/density concentrates, (4) to fight the curse of dimensionality, and (5) to disentangle underlying explanatory factors of the data-i.e., to make sense of the data in the context of an application domain. To address these challenges and to ensure successful machine learning applications in various domains an integrated machine learning approach is important. This requires a concerted international effort without boundaries, supporting collaborative, cross-domain, interdisciplinary and transdisciplinary work of experts from seven sections, ranging from data pre-processing to data visualization, i.e., to map results found in arbitrarily high dimensional spaces into the lower dimensions to make it accessible, usable and useful to the end user.

show abstract

Section: Machine Learning Educationmentioning

confidence: 99%

Introduction to MAchine Learning & Knowledge Extraction (MAKE)

Holzinger¹

2017

MAKE

View full text Add to dashboard Cite

show abstract

“…A number of research groups have developed methods to implement a chosen set of ethical rules in robots (e.g., [7,8,44,61,63,64]). Currently, this field is in its infancy [26]. However, progress is encouraging, and the field can be expected to develop over the next few years.…”

Section: Which Ethical Rules?mentioning

confidence: 99%

Can We Agree on What Robots Should be Allowed to Do? An Exercise in Rule Selection for Ethical Care Robots

Vanderelst

Willems

2019

Int J of Soc Robotics

View full text Add to dashboard Cite

Future Care Robots (CRs) should be able to balance a patient's, often conflicting, rights without ongoing supervision. Many of the trade-offs faced by such a robot will require a degree of moral judgment. Some progress has been made on methods to guarantee robots comply with a predefined set of ethical rules. In contrast, methods for selecting these rules are lacking. Approaches departing from existing philosophical frameworks, often do not result in implementable robotic control rules. Machine learning approaches are sensitive to biases in the training data and suffer from opacity. Here, we propose an alternative, empirical, survey-based approach to rule selection. We suggest this approach has several advantages, including transparency and legitimacy. The major challenge for this approach, however, is that a workable solution, or social compromise, has to be found: it must be possible to obtain a consistent and agreed-upon set of rules to govern robotic behavior. In this article, we present an exercise in rule selection for a hypothetical CR to assess the feasibility of our approach. We assume the role of robot developers using a survey to evaluate which robot behavior potential users deem appropriate in a practically relevant setting, i.e., patient non-compliance. We evaluate whether it is possible to find such behaviors through a consensus. Assessing a set of potential robot behaviors, we surveyed the acceptability of robot actions that potentially violate a patient's autonomy or privacy. Our data support the empirical approach as a promising and cost-effective way to query ethical intuitions, allowing us to select behavior for the hypothetical CR.

show abstract

“…Currently, this field is in its infancy [1]. Indeed, working out how to build ethical robots has been called "one of the thorniest challenges in artificial intelligence" [7]. But promising progress is being made and the field can be expected to develop over the next few years.…”

Section: Introductionmentioning

confidence: 99%

The Dark Side of Ethical Robots

Vanderelst

Winfield

2018

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society

View full text Add to dashboard Cite

Concerns over the risks associated with advances in Artificial Intelligence have prompted calls for greater efforts toward robust and beneficial AI, including machine ethics. Recently, roboticists have responded by initiating the development of so-called ethical robots. These robots would, ideally, evaluate the consequences of their actions and morally justify their choices. This emerging field promises to develop extensively over the next years. However, in this paper, we point out an inherent limitation of the emerging field of ethical robots. We show that building ethical robots also necessarily facilitates the construction of unethical robots. In three experiments, we show that it is remarkably easy to modify an ethical robot so that it behaves competitively, or even aggressively. The reason for this is that the specific AI, required to make an ethical robot, can always be exploited to make unethical robots. Hence, the development of ethical robots will not guarantee the responsible deployment of AI. While advocating for ethical robots, we conclude that preventing the misuse of robots is beyond the scope of engineering, and requires instead governance frameworks underpinned by legislation. Without this, the development of ethical robots will serve to increase the risks of robotic malpractice instead of diminishing it.

show abstract

Machine ethics: The robot’s dilemma

Cited by 77 publications

References 4 publications

Introduction to MAchine Learning & Knowledge Extraction (MAKE)

Introduction to MAchine Learning & Knowledge Extraction (MAKE)

Can We Agree on What Robots Should be Allowed to Do? An Exercise in Rule Selection for Ethical Care Robots

The Dark Side of Ethical Robots

Contact Info

Product

Resources

About