ΑΙhub.org
 

ACM statement on facial recognition technology


by
01 July 2020



share this:
ACM logo

The Association for Computing Machinery (ACM) U.S. Technology Policy Committee (USTPC) released a statement on 30 June calling for “an immediate suspension of the current and future private and governmental use of FR [facial recognition] technologies in all circumstances known or reasonably foreseeable to be prejudicial to established human and legal rights.”

In the document, the ACM write:

The Committee concludes that, when rigorously evaluated, the technology too often produces results demonstrating clear bias based on ethnic, racial, gender, and other human characteristics recognizable by computer systems. The consequences of such bias, USTPC notes, frequently can and do extend well beyond inconvenience to profound injury, particularly to the lives, livelihoods and fundamental rights of individuals in specific demographic groups, including some of the most vulnerable populations in our society.

Such bias and its effects are scientifically and socially unacceptable.

The USTPC find that, at present, facial recognition technology is not sufficiently mature and reliable to be used fairly and safely. Systems have been adopted by governments and industry before the necessary regulation and guiding principles have been put in place.

Therefore, the USTPC call for urgent development of standards and regulation and provide a list of guiding principles in the document. These cover the areas of accuracy, transparency, governance, risk management and accountability. Their recommendations include:

  • Before a facial recognition system is used to make or support decisions that can seriously adversely affect the human and legal rights of individuals, the magnitude and effects of such system’s initial and dynamic biases and inaccuracies must be fully understood.
  • When error rates are reported, they must be disaggregated by sex, race, and other context-dependent demographic features, as appropriate.
  • A facial recognition system should be activated only after some form of meaningful advance public notice of the intention to deploy it is provided and, once activated, ongoing public notice that it is in use should be provided at the point of use or online, as practicable and contextually appropriate. These notices should contain a description of the training data and details about the algorithm.
  • No facial recognition system should be deployed prior to establishing appropriate policies governing its use and the management of data collected by the system.
  • No facial recognition system should be made available or deployed unless its relevant material risks to vulnerable populations, or to society as a whole, can be sufficiently eliminated or remediated.
  • When harm results from the use of such systems, the organization, institution, or agency responsible for its deployment must be fully accountable under law for all resulting external risks and harms.

You can see the full list of recommendations and read the ACM USTPC statement in full here.




AIhub is dedicated to free high-quality information about AI.
AIhub is dedicated to free high-quality information about AI.




            AIhub is supported by:


Related posts :



coffee corner

AIhub coffee corner: Agentic AI

  15 Aug 2025
The AIhub coffee corner captures the musings of AI experts over a short conversation.

New research could block AI models learning from your online content

  14 Aug 2025
The method protects images from being used to train AI or create deepfakes by adding invisible changes that confuse the technology.

What’s coming up at #IJCAI2025?

  13 Aug 2025
Find out what's on the programme at the forthcoming International Joint Conference on Artificial Intelligence.

Interview with Flávia Carvalhido: Responsible multimodal AI

  12 Aug 2025
We hear from PhD student Flávia about her research, what inspired her to study AI, and her experience at AAAI 2025.

Using AI to speed up landslide detection

  11 Aug 2025
Researchers are using AI to speed up landslide detection following major earthquakes and extreme rainfall events.

IJCAI in Canada: 90-second pitches from the next generation of AI researchers

  08 Aug 2025
Find out about some of the interesting research taking place across Canada.

AI for the ancient world: how a new machine learning system can help make sense of Latin inscriptions

  08 Aug 2025
System retrieves textual and contextual parallels, makes use of visual details, and can generate speculative text to fill gaps in inscriptions.

Smart microscope captures aggregation of misfolded proteins

  07 Aug 2025
EPFL researchers have developed a microscope that can predict the onset of misfolded protein aggregation.



 

AIhub is supported by:






©2025.05 - Association for the Understanding of Artificial Intelligence


 












©2025.05 - Association for the Understanding of Artificial Intelligence