Content prioritization – as a resorting algorithm- means deciding what information are most important and should be displayed first or received more attention. For a correct understanding of this term, it may be helpful to state some concrete examples in everyday life.

Chain stores increase sales by creating an attractive display, using window displays effectively, and highlighting discounts. Strategic placement of discounted products helps improve the shopping experience. Seasonal adjustments are also done to keep customers’ attention. Stores also, considering the customers’ interest in a specific type of product, place it more prominently in view or at the store entrance. Similarly to computer science world, stores consider the sales volume and people’s preferences, rearrange, and update the layout of supermarket products, aligning with past seasonal sales. In chain stores like Walmart or Safeway, these arrangements are simultaneously implemented across all branches.

In computer science, it could involve organizing a website to showcase crucial buttons at the top or arranging files to find easily. In computer science, it’s about choosing what information to showcase first. It’s like putting the most important stuff upfront for a better experience.

Major online platforms like Facebook, Google, and others have transformed the world, but they have some social disadvantages like racial discrimination and misinformation due to reducing information privacy. Black and Brown people are vulnerable against equitable opportunities in housing, employing, and studying due to biased data. Low-income people may decline privacy protections due to use cheap data-secure devices and services. Currently, personal information, particularly residential addresses, can be used to determine socioeconomic status. (Allen, 2022). For example, the algorithm used to estimate kidney function is developed from biased data sets or rely on incorrect assumptions. There is a concern that it results in care disparities for racial and ethnic minority groups. This healthcare algorithm shows Black people have healthier kidneys compared with White people. So Black people’s access to kidney transplants is restricted. (Jain et al., 2023). Also, face recognition algorithms with high classification accuracy  has a divergent error rates in female, Black and 18-30 years old (Najibi, 2020).

In my professional work as a research assistant, I use google to find new information about tools that we use in our lab. Google search engine put big companies in the top of its result list. Based on this type of algorithm, new start-ups lose the opportunity to participate in marketing and the market is monopolized by a few big corporations. I trust the results of this hierarchical research algorithm, but I heard that some companies or persons by paying a fee could be moved to the top of the search list. As a result, trust in the results could be shaken. Also, I usually use university library and some professional scientific website. Sometimes, I use google scholar to complete or check my search from other websites. I do not consider any evidence of discrimination in this filed. However, it should be kept in mind that English-language journals and journals published by European and American centers are more accessible in the initial search than journals published from other parts of the world. So, this can lead to discrimination in the reading and referencing of such articles.

PageRank

PageRank is a google algorithm to display search results based on some defined order. In network world, increasing the PageRank score of a web page will mean that page is more visible and place higher than other pages in a search list.

In personal life, this algorithm helps me to find more match results based on my search. For example, in online shopping, based on my keywords and filters, it presents me the best quality and good price products and more reliable buy/sell sites. Therefore, by trusting its scaling, I not only get the goods with high quality and reasonable price, but also save my time. Or, for example, when choosing a restaurant to have dinner with the family, with a quick search, in addition to the suitable restaurant in terms of space ranking and other facilities, you can even choose the most favorite food of that restaurant. However, these results sometimes could be popular not factual because some companies offer to sell high PageRank links. Another example is searching for the most watched movies of year. PageRank with the list of active websites in the field of movie based on the most used site, makes it possible to avoid wandering in checking multiple sites and not finding the desired result. But we should be aware of its limitations such as older pages may have higher rank (“PageRank,” Feb 5, 2024) or uncontrolled posting of spam links (“Limitations of PageRank,”).

Not only PageRank impacts our life, maybe we can impact it. We need to remember that changing the PageRank is not directly in our control. PageRank is changed algorithmically based on the quantity and quality of its incoming links. But we can indirectly contribute to a website’s online presence like as sharing the website’s content on social media to increase its visibility, or if we have a personal website (or blog, I am not sure it works) we can link to the other sites to increase their visibility and ranks.

Reference:

Jain, A., Brooks, J. R., Alford, C. C., Chang, C. S., Mueller, N. M., Umscheid, C. A., & Bierman, A. S. (2023). Awareness of Racial and Ethnic Bias and Potential Solutions to Address Bias With Use of Health Care Algorithms. JAMA Health Forum, 4(6), e231197. https://doi.org/10.1001/jamahealthforum.2023.1197

Limitations of PageRank. https://salomewairimu.github.io/essays/pagerank.pdf

Najibi, A. (2020). Racial Discrimination in Face Recognition Technology. Blog, Science Policy , Special  Edition : Science, Policy, and Social  Justice https://sitn.hms.harvard.edu/flash/2020/racial-discrimination-in-face-recognition-technology/

PageRank. (Feb 5, 2024). Wikipedia, the free encyclopedia. https://en.wikipedia.org/wiki/PageRank

Human intelligence vs. Artificial intelligence

References:

AI pioneer Marvin Minsky dies aged 88. (2016). https://www.bbc.com/news/technology-35409119

Editors, B. c. (2020). Alan Turing Biography. A&E; Television Networks. https://www.biography.com/scientists/alan-turing

Hao, K. (2020). We read the paper that forced Timnit Gebru out of Google. MIT Technology Review. https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru

Herbert A. Simon. https://en.wikipedia.org/wiki/Herbert_A._Simon

Herbert Simon. https://www.ubs.com/microsites/nobel-perspectives/en/laureates/herbert-simon.html

Horowitz, A. H., Esfahany, K., Gálvez, T. V., Maes, P., & Stickgold, R. (2023). Targeted dream incubation at sleep onset increases post-sleep creative performance. Scientific Reports, 13(1), 7319. https://doi.org/10.1038/s41598-023-31361-w

John McCarthy – computer scientist. https://en.wikipedia.org/wiki/John_McCarthy_(computer_scientist)

Kumar, H., & Martin, A. (2023). Artificial Emotional Intelligence: Conventional and deep learning approach. Expert Systems with Applications, 212, 118651. https://doi.org/https://doi.org/10.1016/j.eswa.2022.118651

Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017). Building machines that learn and think like people. Behav Brain Sci, 40, e253. https://doi.org/10.1017/s0140525x16001837

Tsujii, J. i. (2011, 2011//). Computational Linguistics and Natural Language Processing. Computational Linguistics and Intelligent Text Processing, Berlin, Heidelberg.

Turing, A. (1950). Computing Machinery and Intelligence. Mind, 49, 433-460. https://redirect.cs.umbc.edu/courses/471/papers/turing.pdf

Vygotsky, L. S. (1978). Interaction between learning and development. Mind and Society, 79-91.

Zou, J., & Schiebinger, L. (2018). AI can be sexist and racist – it’s time to make it fair. Nature (London), 559(7714), 324-326. https://doi.org/10.1038/d41586-018-05707-8

Mostly, usability is described in the context of human-technology interaction. Usability is not an independent entity; rather, it is considered as part of an ongoing process -a continuous cycle of production, evaluation, and reproduction. From the user’s viewpoint, usability means carrying out a task accurately and with enjoyment. It must be simple to learn, easy to use, and minimizing errors. Technology specialists consider usability in terms of organizational, social, and psychological factors during the design process and quality assessment.

Educational products should not only be easy to use but also support teaching strategies and learning outcomes. Educational environments are characterized by diverse learners with varying needs and abilities. In the realm of education, users fall into two distinct groups with different needs. The first group comprises teachers who use educational technology for teaching. Since these technologies are at their disposal throughout the teaching period, they actively provide feedback. The second group consists of students who use these tools for completing assignments and studying. Here, two issues arise: firstly, at each educational level, a student typically uses the tool only once, and they won’t revisit it, leading to less inclination to provide feedback. Furthermore, the disparity in individuals’ awareness at a particular educational level can result in diverse opinions, making it challenging to derive comprehensive feedback. Therefore, there is a need for a shift towards a student-centric approach in the future.

There is a need for redefining usability concerning instructional methods. Educational usability is a comprehensive framework that goes beyond traditional usability concepts and focuses on instructional design models with pedagogical objectives, user-centered design, feedback mechanisms, and assessment features. System designers for educational products often rely on the feedback from teachers and a small group of students. This limitation can potentially lead to significant differences in the usability of their products.

In reviewing Woolger’s article, several examples show that a usability study could end up configuring users. For example, he demonstrated that “Observers frequently intervened to explain the origin of a problem in terms of a machine fault, where this prevented (or made difficult) the completion of the task by the subject.” ¹ (Page 85)

Repeated interventions during testing to correct errors lead to the user’s uncertainty and doubts about the device’s capabilities. It interferes with subsequent actions in the next user’s steps. User dissatisfaction with pressure of frequent interventions causes a lack of focus to follow procedures as an ordinary user. Additionally, the continuous presence of observers decreases the sense of being in the real work environment. The quick intervention of the observers leads to a misunderstanding of the technical problem of the device, not only overlooking the user’s problem but also diverting resources to the support the device. Finally, this feeling in the user reinforces the hypothesis of attributing the problem to the machine rather than the user, so, in the next stages, the observers will have incorrect results of the affected user’s behavior.

The second example involves the impact of confidentiality on the usability process. Due to competition in capturing consumer markets, companies try to disclose the least amount of information about their product until its release. This limitation extends across various stages, from design to production and distribution. Because of this constraint, companies for obtaining feedback from users, must hire non-real users, such as someone inside the company or experienced college students. This approach interference with the goal of working with beginner users and the obtained results do not perfectly align.

Finally, two quotes (Issa & Isaias, 2015 and Woolgar, 1990) are compared to highlight their differences in the uses of ability. Issa & Isaias’ quote³ about the usability evaluation stage focuses on the stage of usability (it refers to the “quality of the interaction”, “improving methods”, and “assessing effectiveness”) evaluation only restricted to tool making process. It suggests that during development process, the user plays an important role in shaping usability, but this involvement fades or stops after the product is released to the market.

Therefore, there is a timeframe for user’s role, and the company, until the next product does not need any post-market monitoring and evaluation. However, Woogler⁴ believe that for making a new product, there should be special attention to the user’s configuring process from the design time until after releasing it to the market. Thus, it is not a limited timeframe. In this perspective, the user’s role is not only prominent in design and production but should also be considered for long term.

(Words: 741)

1. Woolgar, S. (1990). Configuring the user: The case of usability trials. The Sociological Review, 38(1, Suppl.), S 85.
2. Woolgar, S. (1990). Configuring the user: The case of usability trials. The Sociological Review, 38(1, Suppl.), S 87.
3. Issa, T., & Isaias, P. (2015)Usability and human computer interaction (HCI).In Sustainable Design (pp. 29). Springer. “
4. Woolgar, S. (1990). Configuring the user: The case of usability trials. The Sociological Review, 38(1, Suppl.), S 59.

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