In recent years, private companies, public sector organizations and academic groups have outlined ethical values that they consider important for responsible artificial intelligence (AI) technologies. However, little is known about the values that a more representative public would prioritize for the AI technologies they interact with and might be affected by. To address this gap in knowledge, a team of researchers conducted a survey examining how individuals perceive and prioritize responsible AI values across three groups: a representative sample of the US population (N=743), a sample of crowdworkers (N=755), and a sample of AI practitioners (N=175). The results of the study empirically confirm a common concern: AI practitioners' value priorities differ from those of the general public. Specifically, compared to the US-representative sample, AI practitioners appear to consider responsible AI values as less important and emphasize a different set of values. This finding highlights the importance of paying attention to who gets to define responsible AI. Interestingly, self-identified women and black respondents found responsible AI values more important than other groups. Surprisingly, more liberal-leaning participants were also more likely to prioritize fairness than other groups rather than participants reporting experiences with discrimination. Overall, these findings suggest that there is significant variation in how different groups prioritize ethical values for responsible AI. As such, it is crucial to engage diverse stakeholders in discussions around defining responsible AI and ensuring that their perspectives are taken into account when developing guidelines and policies for these technologies.
Different groups have different ideas about what is important for responsible AI. Some people care more about certain values than others. It is important to listen to everyone's opinions when making rules for AI.
Definitions
- Private companies: businesses that are owned by individuals or groups of people, rather than the government
- Public sector organizations: government-run organizations that provide services to the public, such as schools and hospitals
- Ethical values: principles that guide behavior and decision-making based on what is right and wrong
- Representative public: a group of people who are similar to the general population in terms of demographics (such as age, gender, race)
- Survey: a study where people answer questions about their opinions or experiences
- Prioritize: to consider something as more important than other things
- Crowdworkers: people who complete tasks online for pay from various sources
- AI practitioners: people who work with artificial intelligence technology
- Fairness: treating everyone equally and without bias
- Discrimination: treating someone unfairly because of their race, gender, or other characteristics
- Guidelines and policies: rules or recommendations for how something should be done
Exploring Responsible AI Values Across Different Groups
In recent years, the development of artificial intelligence (AI) technologies has been accompanied by a growing interest in responsible AI. Private companies, public sector organizations and academic groups have outlined ethical values that they consider important for responsible AI. However, little is known about the values that a more representative public would prioritize for the AI technologies they interact with and might be affected by. To address this gap in knowledge, a team of researchers conducted a survey examining how individuals perceive and prioritize responsible AI values across three groups: a representative sample of the US population (N=743), a sample of crowdworkers (N=755), and a sample of AI practitioners (N=175).
Findings from the Study
The results from this study empirically confirm one common concern: AI practitioners' value priorities differ from those of the general public. Specifically, compared to the US-representative sample, AI practitioners appear to consider responsible AI values as less important and emphasize different sets of values. This finding highlights the importance of paying attention to who gets to define responsible AI.
Interestingly, self-identified women and black respondents found responsible AI values more important than other groups. Surprisingly, more liberal-leaning participants were also more likely to prioritize fairness than other groups rather than participants reporting experiences with discrimination.
Implications for Developing Guidelines & Policies Around Responsible Artificial Intelligence
Overall, these findings suggest that there is significant variation in how different groups prioritize ethical values for responsible artificial intelligence technology. As such, it is crucial to engage diverse stakeholders in discussions around defining what constitutes “responsible” when it comes to developing guidelines and policies for these technologies - taking into account their perspectives on what matters most when it comes to using artificial intelligence responsibly.
Private companies, public sector organizations, and academic groups have outlined ethical values they consider important for responsible artificial intelligence technologies. While their recommendations converge on a set of central values, little is known about the values a more representative public would find important for the AI technologies they interact with and might be affected by. We conducted a survey examining how individuals perceive and prioritize responsible AI values across three groups: a representative sample of the US population (N=743), a sample of crowdworkers (N=755), and a sample of AI practitioners (N=175). Our results empirically confirm a common concern: AI practitioners' value priorities differ from those of the general public. Compared to the US-representative sample, AI practitioners appear to consider responsible AI values as less important and emphasize a different set of values. In contrast, self-identified women and black respondents found responsible AI values more important than other groups. Surprisingly, more liberal-leaning participants, rather than participants reporting experiences with discrimination, were more likely to prioritize fairness than other groups. Our findings highlight the importance of paying attention to who gets to define responsible AI.
