Detroit residents skeptical of AI in city government, survey finds
Support for artificial intelligence in Detroit municipal operations remains weak, with most proposed uses failing to gain backing from a majority of residents, according to a University of Michigan survey released in March.
The Detroit Metro Area Communities Study surveyed more than 2,100 residents last fall. Support topped out at 57% for using AI to identify missing children. Every other application tested fell below 40%: 38% backed AI for monitoring neighborhood upkeep or identifying crime suspects, 34% for city website assistance, and 30% for water and wastewater management.
Opposition was sharpest for crime suspect identification, with 39% against. Water and wastewater management faced 37% opposition.
Data privacy concerns dominate resident hesitation
Residents expressed deep anxiety about sharing personal information. Nearly two-thirds said they would not allow local governments access to their data, even if it improved AI systems. Only 22% would permit it.
Between 40% and 55% of respondents worried that AI could benefit some residents while harming others-a direct concern about algorithmic bias in city services.
Mara Cecilia Ostfeld, research associate professor of public policy at the university and co-author of the report, said residents approached AI adoption "with caution rather than enthusiasm." She added that "concerns about data sharing are particularly pronounced."
Efficiency pitch falls short
Efficiency gains emerged as the most persuasive argument for AI adoption among surveyed residents. Yet even this failed to build broad support. Between 20% and 30% remained neutral on efficiency benefits across different scenarios.
Yucheng Fan, data manager at the Detroit Metro Area Communities Study, said the findings suggest "efficiency alone does not lead to broad public buy-in."
Municipal leaders nationally are moving faster than their constituents. An Euna Solutions survey published earlier this year found 16% of local governments have ongoing AI pilot projects, while less than 2% have broadly deployed AI across departments. Efficiency gains remain the top goal among city leaders exploring the technology.
Building trust requires transparency
The survey revealed high uncertainty about how AI systems would operate in city government. Ostfeld said Detroit leaders hoping to expand AI use should "first build trust by clearly explaining how these systems will be used and how residents' information will be safeguarded."
For government professionals evaluating AI adoption, these findings underscore a critical gap: public acceptance depends on addressing specific concerns about bias, data protection, and system transparency-not just the efficiency case alone.
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