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 :



#AAAI2025 workshops round-up 3: Neural reasoning and mathematical discovery, and AI to accelerate science and engineering

  19 May 2025
We find out about three more of the workshops that took place at AAAI 2025.

What’s coming up at #ICRA2025?

  16 May 2025
Find out what's in store at the IEEE International Conference on Robotics & Automation, which will take place from 19-23 May.

AI Song Contest returns for 2025

  15 May 2025
This year's competition will culminate in a live award show in November.

Robot see, robot do: System learns after watching how-tos

  14 May 2025
Researchers have developed a new robotic framework that allows robots to learn tasks by watching a how-to video

Interview with Ananya Joshi: Real-time monitoring for healthcare data

  13 May 2025
Find out how Ananya worked with domain experts to develop a system to identify respiratory outbreaks.

AI-powered robots help tackle Europe’s growing e-waste problem

  12 May 2025
EU-funded researchers have developed adaptable robots that could transform the way we recycle electronic waste, benefiting both the environment and the economy.

Interview with Onur Boyar: Drug and material design using generative models and Bayesian optimization

  09 May 2025
Find out how Onur is applying machine learning techniques to bioinformatics-related problems.

2025 AI Index Report

  08 May 2025
Read the latest edition of the AI Index Report which tracks and visualises data related to AI.



 

AIhub is supported by:






©2025.05 - Association for the Understanding of Artificial Intelligence


 












©2025.05 - Association for the Understanding of Artificial Intelligence