The Current State of Industrial Practice in Artificial Intelligence Ethics
IEEE Computer Society Team
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The practical applications for the use of Artificial Intelligence (AI) have rapidly spread through numerous industries. However, we are often unaware of how many times we interact with AI technologies each day as we use mobile personal assistants, e-commerce sites, voice-activated devices and applications, online gaming, and so on. We logically expect the development and use of AI to have an increasingly quantifiable influence on human society.
This explosion of applications in various industries that leverage AI systems and technologies has given rise to concerns over AI ethics. Sometimes the failures of AI are unintentional, but there is also rising concern that AI could be misused both intentionally and maliciously. For this reason, it is of interest to determine the current state of industrial practice in artificial intelligence ethics.
AI ethics is still in its developmental stage, but most agree that it should be founded on three key principles:
Accountability. This applies not only to those who develop technology but also to stakeholders such as owners, investors, and so forth. Accountability will ensure that all involved accept responsibility.
Responsibility. Along those lines, being responsible means acting ethically and promoting fairness and trust.
Transparency. Development, data, algorithms, and the technical aspects of an application should be transparent. This transparency encourages those involved to be aware and conscientious about the use and results of AI technology.
What Is the Current State of AI Ethics in the Industry?
A recent survey of 211 software companies produced mixed results, revealing that while there is a level of awareness of the need for standardized AI ethics, increased awareness is needed to raise the status quo. Organizations require a starting point if they intend to implement AI ethics, and staff would need to be trained and educated. This would give rise to certain best practices and help companies avoid common pitfalls in implementing AI ethics.