Month: September 2022

ETEC 511 – IP #2: Artificial Intelligence

Posted on by Jon K.

1. Who were these people, and how did/does each contribute to the development of artificial intelligence? How did/does each think “intelligence” could be identified? (~50 words each)

Alan Turing: In the context of artificial intelligence, Turing is best known for developing Turing’s test – which is a game that a computer and a human answer questions with the interregator trying to determine which is human. While this test of “thinking” is a bit limited especially when you consider a computer could be trained to mimic a human response to questions, it is the first ideas of what kinds of qualifications artificial intelligence might require.

John McCarthy: McCarthy is often listed among the parents of the artificial intelligence field. To me, McCarthy is most important for opening up the philosophical problems of AI (McCarthy and Hayes, 1969) and trying to separate intelligence from humanity, and to start to dissect what people mean by intelligence. McCarthy believed that intelligence was the “computational part of the ability to achieve goals in the world”. (McCarthy 1997, in Sutton, 2020)

Herb Simon: Another founding parent of artificial intelligence, Simon drew from his early research into decision making and brought that rationality and requirements for large data to draw an analysis from to the field of artificial intelligence. He was awarded the Nobel Prize in Economics in 1978 for his work on how people make decisions when they have incomplete information.

Marvin Minsky: Minsky in 1960 wrote about how artificial intelligence needed to address problems from multiple perspectives. He viewed artificial intelligence as a complex problem solving divided into five main processes: search, pattern recognition, learning, planning and induction. Minsky believed that when computers were able to take into account each of those aspects, that computers would be considered intelligent.

Timnit Gebru: Gebru was the co-lead of Google’s ethical AI team and was forced out as the result of a paper that suggested that large language models that train AI were often discriminatory. (Hao, 2020) This paper, and the subsequent social media discussion around ethical AI, has ushered in a new dimension to consider when developing AI tools.

2. How do “machine (programming) languages” differ from human (natural) ones? (~100 words).

Harris (2018) writes that the difference between the two languages are that programming languages are completely described, having their own set of rules, and they do not evolve with their usage on their own. I would add two other aspects in that natural language is used to create programming languages, and programming languages need a compiler. Of course, our own natural languages require interpretation (even when using the same natural language).

3. How does “machine (artificial) intelligence” differ from the human version? (~100 words).

If we deem AI intelligence at all, artificial and biological are not comparable. Firstly, artificial intelligence is limited in a myriad of ways that make it overall limited in capacity. Looking at AI art generators – they can function within the programming of the generator. The generator cannot become inspired by another art style. Intelligence is not simply the regurgitation of facts but drawing from different disciplines to develop novel ideas. Secondly, while artificial intelligence operates within parameters with a specific purpose, human intelligence does not. It wanders, it does not simply focus on solving the problem posed to it, but also runs a biological body on top of it.

4. How does “machine learning” differ from human learning? (~100 words) 

Machines do not have the ability to assess the motivation for an author to publish something or discriminate against false information. Essentially because humans can be flawed and discriminatory (or outright racist, sexist or biased) and humans make these algorithms that determine how and on what machines learn, it follows that any bias that might exist in a human programmer, or body of data that trains the machine, would introduce those flaws into the machine. However, a human can correct those flaws (or double down on them) whereas the machine would simply use the programming to “learn” the same facts.

5. And for your LAST challenge, a version of the Turing Test: how do YOUR answers to these questions differ from what a machine could generate? (~200 words)

It all depends? Is the AI trained to draw from the same sources I have drawn (and linked) to? If so, then yes. Is AI likely to draw the same parallels that I see with the power structures that serve as guideposts for society and programming as the guiderails for AI? No. It strikes me that elements of my answers, particularly the answers to question 1, would be easy for a search engine (never mind a paragraph writing AI) to replicate. It might have some issue with the personalization that I tried to provide. In fact, it might give a better answer. Less susceptible to my personal interests in what the author wrote, or what they might have said. The answer to question 5, would probably lead to a variety of interpretations? Or maybe the AI would have a way to answer these sorts of self-examination questions? It reminds me of the Voigt-Kampff test from the movie Blade Runner, which is an empathy test designed to foil AI.

Blade Runner – Voight-Kampff Test

References:

Harris, A. (2018, November 1) Human languages vs programming languages. Medium. https://medium.com/@anaharris/human-languages-vs-programming-languages-c89410f13252

Hao, K. (2020, December 4) We read the paper that forced Timnit Gebru out of Google. Here’s what it says. MIT Technology Review. https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru

McCarthy, J. and Hayes, P. (1969) Some philosophical problems from the standpoint of artificial intelligence. John McCarthy’s Home Page. http://www-formal.stanford.edu/jmc/mcchay69.pdf

Sutton, R.S. (2020) John McCarthy’s definition of intelligence. Journal of Artificial General Intelligence 11(2), 66-67 http://www.incompleteideas.net/papers/Sutton-JAGI-2020.pdf

The Nobel Prize (1978, October 16) The Prize in Economics 1978. The Nobel Prize. https://www.nobelprize.org/prizes/economic-sciences/1978/press-release/

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ETEC 511 – IP #1: Users, Uses and Usability

Posted on by Jon K.

1. Formulate a conception of usability (based on the Issa and Isaias (2015) chapter on HCI and Usability). Use what you’ve learned about usability from that chapter—but you are not summarizing or repeating their ideas. Rather, you are setting out the idea of ‘usability’ you have put together from reading that chapter. Do NOT overly rely on quotes. And remember to use proper citation practices. If you are using text that is not your own, quote and cite it, including page numbers.

HCI (Human Computing Interaction) is essentially a translation service, in that it attempts to communicate between a machine and a human the purpose of the machine. Usability is the measurement of the success of that translation. If a piece of software or website is usable, then it is described as intuitive, easy to use, simple. To be usable, a designer must examine the functionality, efficiency, effectiveness of the software and take into consideration the user’s needs, context and satisfaction. (Issa and Isaias, 2015, p. 30) While this article was written only seven years ago, it seems like the authors only consider positive usage of technology and do not consider, or consider deeply, the idea of designing around bad actors. Wiegers contends that you should design around bad actors, and to prevent users from possibly misconstruing the information conveyed – in that usability should factor in not only the positive uses of a system, but also how it can be misused. (Wiegers, 2021)

2. Then, think about what is missing from this conception, from a specifically educational perspective, and on that basis try and patch together a reasonably grounded and defensible conception of educational usability.

While usability is a key concept in designing learning – especially the examination of context, and user/student needs, it is missing two other key components. While Issa and Isaias (2015) suggest that the user factors in HCI include motivation, enjoyment and experience level (p. 28) it does not adequately address cultural factors of the user/student. While culture will contribute to levels of access and equity, these factors are often great indicators of success in an educational context. This framework is very much built on western ways of knowing and draws from behaviourist theories of development. For instance, when the designed system works, the user is rewarded (by receiving information, having the computer complete a task, etc.). There is no real opportunity to design for remediation and it appears to have a very binary approach to solving complex problems.

3. Revisit Woolgar’s (challenging but rewarding!) account of “usability gone wrong,” which demonstrates several ways a usability study ended up configuring ‘users,’ thereby undermining the usefulness of usability. Identify and discuss 2 of Woolgar’s examples.

At the crux of Woolgar’s arguments of configuring the user during usability trials it was particularly interesting how he suggested that physical location of user testing is a factor in the results of the testing. Of course, when conducting research, you try to control those variables, and it is very clear (to me) that usability testing is far less rigorous than controlled, double-blind research. However, Woolgar (1990, p. 78) recounts how recalling computer features at Brunel University was different than when in the Stratus offices. If we take this as a common occurrence across users, then how we interact with computers will be different based on physical location. So, it follows that bringing users into a testing area to gather feedback on usability will be different than if the device were provided in their usual operating environment.

A second instance of configuring the users is the selection of who is eligible to participate in user testing (Woolgar, 1990, p. 83) – in this case it is noted that often early adopters, and people who are predisposed to like the product would be ideal testers. However, it is entirely unlikely that these people would provide you a new user’s perspective, or someone who was predisposed to not like computers, or be unfamiliar with computers. In fact, the opposite would likely be the case – users who were familiar and comfortable with computers. It only follows that someone who was familiar with computers would be at least more capable of using them, having a concept of what to do with them.

4. Finally, discuss the two excerpts quoted at the top of this IP, that have been drawn from your readings for this unit, and discuss differences you see in these 2 positions on the uses of usability.

Issa and Isaias (2015) are suggesting that user testing is a feedback mechanism to further improve software and hardware and Woolgar (1990) is suggesting that user testing is a confirmation mechanism – to confirm the assumptions made in designing software and hardware. I see both of these linked to a philosophical debate as to the role of computers in human’s lives – whether humans control computers, or computers determine the actions of humans – and the truth is somewhere in the middle.  It is dependent on your role with the computer. Computer programmers control what is possible and what is not within a game, or website. Human users subvert those possibilities through speedruns and other bending of the rules that humans put in place in the first place. Usability in the early days of computing would never have envisioned some of the ways people would have used computers.

References

Issa, T., & Isaias, P. (2015). Usability and human computer interaction (HCI) In Sustainable Design (pp. 19-35). Springer.

Woolgar, S. (1990). Configuring the user: The case of usability trials. The Sociological Review, 38(1, Suppl.), S58-S99.

Wiegars, K. (2021). Designing around bad actors and dangerous actions. UX Collective. https://uxdesign.cc/designing-around-bad-actors-and-dangerous-actions-8fc7984c510d

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ETEC 511 – Truth and Reconciliation

Posted on by Jon K.

The project brief was to find a document and explore how it portrays indigenous and First Nations peoples – and while it might have been easy to pick something historical, where you would judge the historical figure outside of the time, I thought that I would take on something from my lifetime.

The document I chose: People of Native Ancestry, A Resource Guide for the Primary and Junior Divisions (students).

I chose this document for a few reasons. One key reason being that it is a document from my lifetime and I certainly would have experienced the suggestions of this document from 1975 in my early elementary schooling experience (I started kindergarten in 1978). I am curious to understand the thinking of how teachers would have been instructed to teach about indigenous peoples during the time, and how my experience and admittedly limited understanding of the local Six Nations people growing up might have been reflected in this document. I really do not recall any of the lessons, or even if they were delivered.

This document serves two purposes. One, to help teachers understand and teach people with Indigenous ancestry and two, to teach “[a]s all Ontario children grow in their knowledge of native peoples, both native and non-native people will benefit. Tolerance in a multi-cultural society is built upon active participation in the process of learning about cultures other than one’s own.” (p. 8).

In searching the document the following terms were used to describe indigenous people(s):

IndianIndigenousAboriginalFirst NationsNativeNon-Native
619411

Specific Nation Mentions:

Cree: 9

Mohawk: 6

Ojibwe: 10

Algonquin: 1

One strong theme that arose throughout the writing is the othering of indigenous peoples. They were to be recognized as distinct, but the text treats indigenous people as if there was little to no history between indigenous and white people (outside of the foreward by Chief Dan George of the Burrard Indian Reserve, and the Appendix A, which spans 2 and a half pages -with a paragraph of veritable whitewashing of residential schools, which likely some parents might have experienced). How can one attempt to integrate into a “multi-cultural” society without at least a deeper understanding of history, and the injustice of the history which had been happening for (at that time) hundreds of years, is in modern context, unthinkable.

One other theme, and it is probably a key thing to note, this being a government document, it has chosen to use Native rather than any other language. Indian came up as part of a historical quote, or in the context of naming an act of Parliament or group. In fact Native was the most common reference, and when other children were mentioned they were non-Native. The act of constantly comparing, as if non-Native children might not have their own complexities, histories, familial demands, and approaches to learning and authority. There was a subtle, but present, holding up of (ostensibly white male) children as ideal, and Native as other. In many ways, the othering that was done throughout the document, undermines the front-and-centering of indigenous children by acknowledging their indigenousness. It is definitely a subtle thing, but definitely present.

ETEC 520 – Planning and Managing eLearning

Posted on by Jon K.

Taking this course was a mistake. Well, for me it was. You might need the information. There were a few moments of learning, but for me, who plans and manages “elearning” (whatever that means) as a daily activity, the course was frustrating as it lacked the nuance of the day-to-day, it placed the institution at the centre of the planning when in reality, in my experience this is not planned at the institutional level – it requires a grassroots approach for many years before the institution codifies and standardizes it. The assignments were almost too focused on institutional needs (and I understand why they went this route with the design) – but in all likelihood, only a few of your graduates are going to be at that institutional level to influence change and by the time they get there, Tony Bates’ book will be horribly out of date and the lessons learned will not apply. I also never really got into a rhythm with this course. I’d literally read the readings on Monday, then think for four or five days, I’ve got to do the discussion…. Some weeks I couldn’t even do that. This course, for whatever reason broke my spirit. I’m not egotistical enough to suggest I know it all, I don’t. I think I never was able to connect the readings to the assignments, and the things that we were to do in the class didn’t ever really gel for me. Some of the gaps in the content were glaring for me as well.

In one assignment there’s an elearning readiness check – which assumes that the institution wants to engage in elearning at all! They can’t be ready if they don’t want to do it…. Then the tools that we could use to “assess” readiness were outdated and almost laughable. There was no mention of diversity, equity, accessibility or privacy in any of the assessment tools. Security was an afterthought. Interoperability, standards… those were not addressed as well. Cost was reduced to a line-item. Those are requirements in 2022, as in not optionals or nice to have, but as an institution you must look at technology and learning through those lens’. For a course to just skip over these issues is a bit disheartening.

Even if the assessment tools didn’t have those present – it’s easy to build that into the course by redesigning it to instead have the student design the readiness tool (which then releases the faculty from the dating of the material and the readings can be updated without requiring re-writes of the assessments) and build common factors through discussion and then design a “rubric” for assessment. Make that your first assignment. The second assignment is to look at implementation plans that are available. Analyze them for how your rubric might apply. This rubric could also be used for an RFP like scenario outside of the curriculum. Then re-write the rubric to address any gaps seen in implementation plans. Show some other rubrics. Critique the rubric as your final piece. Or have a reflective piece. Then you have a student-driven, student-centred course.

Admittedly I coasted through and put little effort into this. So I did the required minimum, slowly faded from discussions (which I hate when they’re so structured and stilted and non-organic). This wasn’t a fault of the course, it’s well designed, and was delivered by a facilitator that seemed to care (I would write truly cared, but I don’t know if that’s true or not). I, as a student, did not care. And for that I am sorry somewhat, because I should’ve been able to find a moment or a spot to hold up as worthwhile, but I couldn’t find that spot. So in some ways I failed this course, not marks-wise, but failed to be a good contributor. I was really disheartened by the lack of modern resources. I was really disappointed that this class, that I was honestly looking forward to at the beginning, was really frustrating for me. I can taste how close this is to a useful class for the modern context, but it just falls short. In a little bit of hindsight, it’s probably just a course that’s been in need of a refresh and probably is due up for a change shortly (fingers crossed!).

Oh, and to top it all off, I reused an APA cover sheet from a previous course, and the first time I copied it I didn’t know how to spell the facilitator’s name, so I gave it shot – as a placeholder – with the intention of correcting it later. I never did. To compound my utter stupidity, I submitted it, not once but twice, because the second time I just reused the same cover sheet and didn’t even bother checking. I did pull it together for the last submission, and sent off a mea culpa letter to the prof just to let them know I’m an idiot.

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