Dangers and Recommendations of Algorithms

 

By Lilian H. Hill

A lot of uses of algorithms are beneficial; however, there are dangers involved. Decisions about admissions, scholarship awards, and hiring have been turned over to algorithms. Flaws in programming can cost individuals the opportunity to attend their college of choice because their entrance exams were graded based on a faulty metric. Hiring decisions can be negatively influenced if metrics involved are biased against minorities. People’s privacy can be violated if the algorithms designed to share individual’s information are inaccurate. 

In an interesting news story, Northeastern University installed heat sensor devices undergraduate students’ desks to track usage (Ongweso, 2022). Given that the students were enrolled in Northeaster’s Cybersecurity and Privacy Institute, it should not be surprising that the students detected the presence of the devices, hacked into them, developed an open-source guide so that other students could hack them. They then removed the devices and displayed them in an art exhibit spelling the word NO! The university had installed the devices at night without informing the students and without Institutional Review Board (IRB) permission. The students found that the devices were not as secure as the university claimed. 

Recommendations

The Center for Democracy and Technology recommends the following:

• Human beings need to retain control of decision-making that involves people’s privacy, safety, and opportunities. Context and nuance are difficult to program into algorithms. 
• Regulate data governance: Establish policies that determine long information should be kept and under what certain conditions it should be deleted.
• Conduct regular audits to ensure that discriminatory outcomes or other unexpected harm do not occur.
• Communicate regularly with stakeholders to provide feedback and address concerns about the systems that affect their schools.
• Use algorithms for the purposes they were designed for. Adapting them to other purposes has the potential to yield harmful results.
• Foster accountability by developing plans and policies to identify and correct errors in the programming. Have strategies and resources available to make amends when errors have been harmful to people. 
• Ensure legal compliance so that the decisions made by algorithms are fair, accurate, and comply with legal standards for education. 

References

Center for Democracy and Technology. Algorithmic systems in education: Incorporating equity and fairness when using student data. Retrieved from https://cdt.org/insights/algorithmic-systems-in-education-incorporating-equity-and-fairness-when-using-student-data/ 

Ongweso, E. (2022, December 2). ‘NO’: Grad students analyze, hack, and remove under-desk surveillance devices designed to track them. https://www.vice.com/en/article/m7gwy3/no-grad-students-analyze-hack-and-remove-under-desk-surveillance-devices-designed-to-track-them

 

Algorithms and Culture: A Complex Concept

 

As algorithms permeate many aspects of everyday life. Algorithms influence culture. On this episode, Dr. Lilian Hill discusses the relationship of algorithms and culture. Listen to the episode and join in the discussion.

Listen to the Podcast

Information Literacy Episode 5 Transcript

 

References

Carah, N. (2017, August 16). Algorithmic culture and machine learning. http://nicholascarah.com/log/2017/8/15/algorithmic-culture-and-machine-learning

NBC. (2023 January 1). Meet the Press - January 1, 2023. https://www.nbcnews.com/meet-the-press/meet-press-january-1-2023-n1302274  

Seaver, N. (2017, November 9). Algorithms as culture: Some tactics for the ethnography of algorithmic systems. https://journals.sagepub.com/doi/full/10.1177/2053951717738104

Striphas, T. (2015). Algorithmic culture. European Journal of Cultural Studies, 18(4-5). https://journals.sagepub.com/doi/full/10.1177/1367549415577392

 

 

Pandemic Applications of Algorithms

 

By Lilian H. Hill

Algorithms were essential in maintaining educational activity during the pandemic isolation that caused many students to learn from home through educational technology. We are only just finding out what has been gained and lost in terms of students’ learning, knowledge, and abilities. I heard a recent NPR report about children entering kindergarten who were lacking in knowledge, social skills, and even fine motor coordination because they had spent so much time interacting with devices (Feiereisel, 2022). Adult students may have similarly lost ground in learning, but the results are much harder to track because adults are learning in more diverse settings and are working toward many different goals).

The OECD (2021) estimates that “many forms of learning, in particular informal learning, were inevitably lost, as workplaces remained physically closed,” educational institutions switched to remote learning, and people were isolating themselves to protect their health. Reliance on technology for educational delivery magnified the digital divide.

References

Feiereisel, A. (2022, December 1). Kindergarten teachers observe speech and physical delays in young students. NPR Radio Broadcast. https://www.wbur.org/hereandnow/2022/12/01/kindergarten-student-delays

OECD (2021, March 25). Adult Learning and COVID-19: How much informal and non-formal learning are workers missing? https://www.oecd.org/coronavirus/policy-responses/adult-learning-and-covid-19-how-much-informal-and-non-formal-learning-are-workers-missing-56a96569/#snotes-d4e393

Why Adult Educators Should be Concerned About Algorithms

 

 

Algorithms are highly efficient at automating laborious functions and have permeated into many aspects of our everyday life, but their characteristics can have devastating consequences. On this episode, Dr. Lilian Hill discusses the characteristics of algorithms and why adult educators should be concerned about them.

Listen to the Podcast

 

Information Literacy Episode 4 Transcript

 

References

Bennett, E. E., & McWhorter, R. R. (2020). Digital technologies for teaching and learning. In T. S. Rocco, M. C. Smith, R. C. Mizzi, L. R. Merriweather, & J. D. Hawley (Eds,), The Handbook of Adult and Continuing Education (pp. 177-186). Stylus.

Dickson, B. (2020, June 10). What makes AI algorithms dangerous? Retrieved https://bdtechtalks.com/2020/06/10/ai-weapons-of-math-destruction/

O’Neill, C. (2017). Weapons of math destruction: How big data increases inequality and threatens democracy. Crown Publishing Group.