Category: Linking Assignment

Richard’s post resonated because there have been times I have wished I had extra eyes and ears to monitor my students and prevent bullying. Just the other day there was one pen and four students all claiming it was theirs. Credit Note could save me the trouble of talking to different people to determine who the pen belongs to. Is the solution to ban outside stationery (the school provides students with writing utensils and stationery so students don’t have to bring anything)? What about free choice, being responsible and learning from mistakes? I feel algorithms don’t have the nuances to allow people to make mistakes and grow from them. I fear these kind of algorithms teach people to follow a guideline without thinking. How can future generations innovate new ideas if they live in fear and are forced to live with black and white values?

 

I responded to Anu’s post because of her comment about algorithms need to be transparent and fair. What does fair mean exactly? Does it mean that everyone should be treated the same? If someone doesn’t show up for their hearing because they need to work to support their family, should they be treated the same as someone who doesn’t show up for their hearing because they were stealing to support their family? I wonder how an algorithm would process this? O’Neil (2017) mentions that the algorithm targets people in poverty. It’s impossible for an algorithm to consider all aspects of a person’s circumstances because at this time not all agencies are linked or even online (for example, hospital records). When an algorithm targets people based on their income or skin colour, it overlooks the underlying issues and perpetuates the biases that the algorithm was created with. I think algorithms can be seen as patterns that seek to repeat these patterns, which is why the same people keep getting pulled into this net. Judges in bail court have limited resources and time, if this is all the information you have, then is it fair to ignore it? Could algorithms be used for preventative measures instead so judges can properly listen to cases?

References

O’Neil, C. (2017, April 6). Justice in the age of big data. IDEAS.TED.COM https://ideas.ted.com/justice-in-the-age-of-big-data/

I responded to Clarissa’s post because some things that she did, such as entering fake personal data, have become part of our daily lives. In the past child predators and kidnappers would want to know your name so they could pretend to know who you are and get you into their van or house. Now marketers and companies use your name to create a false sense of intimacy so they can get you into their stores, website and/or checkout counter. The occult could use your birthday and birth time to see your past and future, which is basically what the algorithms are, but they seem more insidious because they also use that data to manipulate your future decisions, which I suppose the occult could do as well, but the algorithms are everywhere and hard to ignore and so commonplace that they are sometimes unnoticeable.

Grant’s comment to my T9 post made me dive more deeply into the question I asked at the end of Task 9: Perhaps it would be easier to achieve diversity through universal feelings?

His comment made me curious to see his T9 post, which I responded to and posted below.

 

I think we should lean into our differences and try to understand them rather than ignore them.

In more detail, I’d like to talk about my shopping experiences in China. Sometimes the item I want is available but not in the colour I want. I used to say, “No” when asked if I’d like to purchase it in a different colour. Now I say, “That colour is not quite to my liking” because I noticed that the sales associate would giggle. At first I was surprised by the laughter–to me it made no sense because I had not said anything funny and I did not think my pronunciation was bad enough to cause laughter. Then I remembered a tip I had been given during my early days of living in China, people often laugh when they are nervous. By doing this I realized that my answer was too abrupt. I started paying attention to how locals interacted with sales associates and learnt how to say “no” in an inoffensive way. The problem with algorithms is oftentimes people don’t know much about the brains and biases behind the algorithms. What biases do they have? What data did they input and how did they interpret this input? How I interpret the data an algorithm comes up with will be different from how someone else would.

If my cultural blunders could be visualized as an image of me covered in question marks, would the number of question marks lessen as I interact with more locals and increase in number every time I move to a new region? Algorithms can both dictate and influence people’s decisions, but isn’t that the same as human interactions? The more often I interact with a group of people, the more I understand them and the more I might adjust my behaviour to better interact with them, but unlike an algorithm, I can find out the exact reasons behind their behaviours.

Dr Zeynep Tufekci’s (2017) TED talk discusses how the choices algorithms make can affect our emotions and political beliefs. I wonder if algorithms could be designed so people can explore differences like the op-ed section of newspapers? At the same time, I am worried about what I consider to be the darker side of our differences. Do I want to know why some people think the Holocaust is a hoax and why some people are, for example, anti-Semitics? I think it would be helpful to know their reasons so I can better address them, but I don’t want to be exposed to the vitriol that probably exists behind those reasons. If I don’t see that vitriol, could I be misled and misunderstand the impact of those feelings? If I were to design an algorithm that aims to provide a balanced argument, would I overcompensate for my biases and lean too far to the other side? Can technology distinguish between equality and equity? Perhaps they can sometimes, but not all the time. Technology should be something humans interact with, not something that replaces humans.

References

Tufekci, Z. (2017). We’re building a dystopia just to make people click on ads. Retrieved from: https://www.ted.com/talks/zeynep_tufekci_we_re_building_a_dystopia_just_to_make_people_click_on_ads?

I was impressed with Nick’s list because he broke it down by region and it was easy to see that his goal was to represent as many different musical traditions and cultures as possible. At the same time, I feel curation comes from a place of expertise. I’m not a music expert, but I am an expert on my own experiences. If extra-terrestrials have a genuine interest in understanding humans, they would look through the top 10 lists of not just one person, but many and compare them. The enormity of digital information available and the impossibility to archive them all means the information out there is more than what one human life can consume. To make sure these archives are not lost, information should be presented to create curiosity and encourage further reading, like the opinion pages of a newspaper.

Right now the job of archiving online data and information resides in the hands of a few. What criteria do they use to determine what is valuable enough to archive? Could technology and algorithms help archivists archive more online texts?

Below I’ve posted my comment on Nick’s T8 task.

Hi Nick,

I took a different approach from you. While originally I tried to be objective, I ended up choosing tracks based on my own prior background. For example, originally I wanted to talk about how the opening notes of Beethoven’s Fifth Symphony are described as fate knocking, but a quick Wikipedia search showed me how that might not have been Beethoven’s intention at all, and that it was more likely mimicking a yellow-hammer bird’s song. I was torn between which description to choose, the one most popularly believed or the one described as most likely to be true. Sometimes I find it hard to not be subjective. I think if I were to redo this activity, I would make two Top 10 lists, one based on my own preferences and one where I do my best to be objective to see how much or little overlap there is.

Chris’ post made me reconsider how I use emojis, especially the “shared understanding” portion of his post because it made me realise how I tend to use emojis to be indirect in certain conversational contexts.

Another reason I’ve chosen to link Chris’ post is his choice to focus on meaning and words when he translated his summary into emojis, noting that using syllables would make the activity too similar to charades. His point is fair and valid. At first, I felt that method was superior to the one I chose, but after reflecting on my summary, I decided to keep it as is. My summary had a lot of nouns and while there were nicknames that I could have translated using meanings and ideas instead of syllables, I felt that a summary should be as objective as possible. However, I do admit that there is one character who I translated using a nickname that I and many people in the WebSphere have started using.

I responded to Chris’ T6 post with the following comment:

It looks like you summarised a crime show like NCIS?

I know that there were some parts I did not understand, but here’s my interpretation: A baker poisons his rival. His rival seems to make a miraculous recovery from the poisoning but in the end, he dies. The baker accidentally kills his love interest so his love is forever unrequited. A detective team investigates and arrests him for murdering the two people.

To me what you said about using emojis to send a message quickly makes sense. Your first paragraph made me think about how I use emojis. Unlike you, I use emojis in both professional and personal contexts. I only use emojis professionally after someone else uses them, and I often use them when I receive texts from colleagues outside of work because they are quick to send and more polite than sending one word responses. I’m not sure what the shared meaning would be in this kind of context would be.