Search results for "Ai systems"
showing 9 items of 9 documents
The Current State of Industrial Practice in Artificial Intelligence Ethics
2020
As Artificial Intelligence (AI) systems become increasingly widespread, we have begun to witness various failures highlighting issues in these systems. These incidents have sparked public discussion related to AI ethics and further accelerated the on-going academic discussion in the area. High-level guidelines and tools for managing AI ethics have been introduced to help industry organizations make more ethical AI systems, but we currently know little about the state of industrial practice. Have these guidelines been adopted by the software industry for developing AI solutions? Are these failures that make the news just the tip of the iceberg? We provide insights into the current state of p…
Ethics of Artificial Intelligence : Research Challenges and Potential Solutions
2020
Artificial Intelligence (AI) is a rapidly emerging paradigm with many applications in healthcare, industries, and smart cities. However, this rise of global interest in AI has fueled a renewed interest from the public sector and global policymakers. As AI networks (e.g., chatbots, automation systems, and helping agents) are paving their way as interactive household items, a critically important research issue is understanding the ethical impact of these autonomous agents. What is the explanation of the AI decision-making process? What are the legal, societal, and moral consequences of these decisions and actions? Should these AI systems be allowed to make decisions for human beings and to w…
Governance of Ethical and Trustworthy Al Systems: Research Gaps in the ECCOLA Method
2021
Advances in machine learning (ML) technologies have greatly improved Artificial Intelligence (AI) systems. As a result, AI systems have become ubiquitous, with their application prevalent in virtually all sectors. However, AI systems have prompted ethical concerns, especially as their usage crosses boundaries in sensitive areas such as healthcare, transportation, and security. As a result, users are calling for better AI governance practices in ethical AI systems. Therefore, AI development methods are encouraged to foster these practices. This research analyzes the ECCOLA method for developing ethical and trustworthy AI systems to determine if it enables AI governance in development process…
ECCOLA : a Method for Implementing Ethically Aligned AI Systems
2020
Various recent Artificial Intelligence (AI) system failures, some of which have made the global headlines, have highlighted issues in these systems. These failures have resulted in calls for more ethical AI systems that better take into account their effects on various stakeholders. However, implementing AI ethics into practice is still an on-going challenge. High-level guidelines for doing so exist, devised by governments and private organizations alike, but lack practicality for developers. To address this issue, in this paper, we present a method for implementing AI ethics. The method, ECCOLA, has been iteratively developed using a cyclical action design research approach. The method aim…
Lost People : How National AI-Strategies Paying Attention to Users
2021
Abstract. This paper focuses on how major national strategies call attention to the human dimensions of artificial intelligence (AI). All intelligent technologies using AI are constructed for people as either active users or as relatively passive target persons. Thus, human properties and human research should have an important role in developing future AI systems. In these development strategies, it is interesting to pay attention to the underlying intuitive assumptions and tacit commitments. This issue is especially interesting when we think about what governmental working groups say about people and their changing lives in their strategies. The traditional stances adopted in writing nati…
ECCOLA : a method for implementing ethically aligned AI systems
2021
Artificial Intelligence (AI) systems are becoming increasingly widespread and exert a growing influence on society at large. The growing impact of these systems has also highlighted potential issues that may arise from their utilization, such as data privacy issues, resulting in calls for ethical AI systems. Yet, how to develop ethical AI systems remains an important question in the area. How should the principles and values be converted into requirements for these systems, and what should developers and the organizations developing these systems do? To further bridge this gap in the area, in this paper, we present a method for implementing AI ethics: ECCOLA. Following a cyclical action res…
Reports of the AAAI 2019 Spring Symposium Series
2019
Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have already been …
A Multiple Case Study of Artificial Intelligent System Development in Industry
2020
There is a rapidly increasing amount of Artificial Intelligence (AI) systems developed in recent years, with much expectation on its capacity of innovation and business value generation. However, the promised value of AI systems in specific business contexts might not be understood, and further integrated into the development processes. We wanted to understand how software engineering processes and practices can be applied to develop AI systems in a fast-faced, business-driven manner. As the first step, we explored contextual factors of AI development and the connections between AI developments to business opportunities. We conducted 12 semi-structured interviews in seven companies in Brazi…
Designing Ethical AI in the Shadow of Hume’s Guillotine
2020
Artificially intelligent systems can collect knowledge regarding epistemic information, but can they be used to derive new values? Epistemic information concerns facts, including how things are in the world, and ethical values concern how actions should be taken. The operation of artificial intelligence (AI) is based on facts, but it require values. A critical question here regards Hume’s Guillotine, which claims that one cannot derive values from facts. Hume’s Guillotine appears to divide AI systems into two ethical categories: weak and strong. Ethically weak AI systems can be applied only within given value rules, but ethically strong AI systems may be able to generate new values from fac…