Mtg 10/24: Thu-10-Feb-2022

Outline for Today

{"desc"=>"Happy Thursday"}

{"desc"=>"Google search", "url"=>"https://www.google.com/search/howsearchworks/"}

{"desc"=>"Judgment for Computer Professionals (first part)", "vid"=>"https://www.youtube.com/embed/PFcHX0Menno"}

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Transcript

Zoom Audio Transcript

Anything exciting.
Good morning.
Oh, what did you say anything exciting.
Anything exciting happen. Since Tuesday.
knows waiting for the exciting to happen here huh.
Okay. yeah the weather. The weather is nice usually. But the weather's Nice and i'm concerned. about this happening and being February, instead of the middle of March.
yeah it's going to be an icebox outside soon it's already rained so much any ice or any Raina freezes going to be an ice rink yeah.
So. So I guess. If some days when i'm not so. delightfully determined. I can. we're not looking for. Positive and staying positive trying to stay positive. And I think. pandemic is such a. Immediate. issue and there's so much. resistance. That, then I wonder. How. we're going to deal with the climate emergency. The way that needs to be. addressed. But anyway. that's that's enough for for that. And I was reading an article about the snow they've had. To make in Beijing, for the Winter Olympics, because. It typically doesn't snow in Beijing. In the areas where they're running through Winter Olympics. And there is an estimate that there will, that they will have us, I believe, by the end of the Games 1.5 trillion liters of water to make snow. It seems like a lot doesn't it. Well, anyway. i'm. I apologize for. Introducing a somber mood and. well. I think we have to think about these things. But not let it not let them paralyze us from taking action and. Making positive contributions. To our world in our society.
yeah I I read that as well and it said that the the entire or two users about 9000 billion what or liters of water per year and that's more than that so it's just crazy.
yeah. Okay. So why don't we start with attendance. After login. Okay, here we go. Meeting on February 10. wow. That was quick with some of those quicker. Okay, so there's the password for attendance. yeah so talk about the project in a minute. So I want to mention. Since i'm. I guess the contact person for equity diversity and inclusion department. I wanted to mention that there's a talk coming up tomorrow afternoon. importance of clear visibility of stem. or in stem. I thought I copied it from the message. Anyway, so stem science, technology engineering and math. Is everyone familiar with that acronym. Okay. comes up one of my favorite movies. So. i'm. Here, let me actually. give you the link for. Sure it's a zoom. presentation. Okay, so there. You. All the details. And that you register, so you have to register, but it's free and. This is the third seminar in the series.
what's this seminar for.
So. it's really. The title of the talk is the importance of clear visibility of stem. So. we'll talk about equity diversity and inclusion. and So it falls under that. The heading. So.
Professor, can I ask you a question about that sure, so a little controversial maybe. But do you think that is more important than the most capable person for the job.
If I could. I could add something. Sure um so like where I work and, like usually in like in high school that kind of thing being like a visible minority in a category. I find that when there are like policies in place to you know, encourage a certain group of people, whether it be ethnicity or or. or sexual orientation that kind of thing. And when you encourage it, it kind of creates this. Air stigma around that group, because now, when you do get to a position people ask whether or not you got there because of this policy, or because of your actual merits, and I find it does more harm than good, usually, when there are policies in place to do that.
And that the opposite is also true, I know. My aunt and uncle they. When they were searching for jobs when they first came to Canada they had. Very a lot of difficulty just because there was a lot of silent racism again some people wouldn't hire them because of their fat strong accent, and they. So. policies such as this can help them get their foot in the door and get jobs when, otherwise they can be blocks or held back from these positions. And the people who often say things such as Oh, they didn't really deserve it. Oh, maybe there's someone else who's better. are often missing the point that a lot of these people. With have struggled. To get these positions due to. system it's just somatic racism in the first place, so these are working to counteract that it's not perfect or ideal but. If it was prefer deal we wouldn't need these policies in the first place.
I agree with hunter.
So.
back to the importance of visibility instead.
A lot of times these like quotas of, say, like a visibility of minorities and arrest may not even taken seriously like sometimes when companies are posting their staff like. With these part of these minorities, they were only like one or two and the rest of them are like part of this of the cysts or the the other race then they're never like actually part of the minorities done much they just do the bare minimum, so they can meet the quota.
Oh yeah just to keep up the image.
Okay.
So, which encourages images, instead of marriage.
mm hmm.
yeah.
same with all of the companies and then not. well. provide the spirit of the law or going through the word of loss, they can do the bare minimum, instead of trying to achieve the spirit of the law, which is. Something that I believe should be punished and or law should be more strict on trying to enforce our should be. Like.
there's a recent issue with. Biden seeing is going to elect a female judge that is black or judges black was, but a lot of people, a lot of like. People in the black community are saying that I wouldn't want to become a judge from Biden just because you would start to question yourself to it was because of your skills are just because they just want REP representation so even when it comes down to it, it's a good thing, but. it's we should be at a point in our world where we don't need these things, or it shouldn't be so openly. put out there you have to have a quota to meet because, once you start putting like terms on people. Everything falls apart.
Well then, there should be something put in place at the base level. or like at the education level where there's a certain I hate the word quota for this, but because I can't think of anything else. there's a quota to meet for certain ethnicities and groups and sexual orientations that. They need to pass a certain amount in school, and then the deciding factor shouldn't be well, are you a part of that minority to get hired or not. Because there's enough in the field that would saturate it instead of all there's barely anybody in the field is pick the only one that's you know of the LGBT part part of me that, with the other minorities right.
A little true. Ideally, everything will be based on merit and not race or ethnicity and gender preferences, but there's a lot of silent racism it's. Companies are often they won't say that because your. Your skin color you're. Just sexual preferences, but it's still a fact that. it's so much harder for someone to get a job if there. are different experts to see if they have an accent if they don't pronounce things of that nature and so policies such as this are. Important to get people in the workforce to get them up there, and if it's not it's not perfect, but once people get into those positions. Those policies slowly become less needed because well if the people hiring you are black Hispanic from the Philippines if they're gay or bisexual or. of everything like that, then you don't need those policies, because the people hiring you. have already in that group so policies such as this, I believe, are working towards a ideal scenario scenario where. They are no longer needed. And that's one of the reasons why I consider them to be important they're working towards. not be needed anymore.
Discrimination is never was a way to fight discrimination right.
yeah.
I feel like there's a fundamental issue with how interview process goes like for like, if you want to enter a music school, they have to do blind auditions because of how much discrimination is there, so I feel like they should try to find a way to implement that approach in the workforce. client interviews.
And I believe that's actually been done a little bit, I think it was Australia, but there's definitely some larger corporations that have done completely blind resumes and interviews you pretty much take off all of your identifying information. I don't know if they give you a number or exactly how it's done. But essentially you take off anything that could be used to identify you your background and they proceed with all the interviews and hiring decisions based on that.
um one thing i'd like to add, is, if you think about it, statistically to like let's say a certain population of minority is 10% of the general population. Then you have everyone else, and then there's a quota for 20% of the workforce to be of that minority status or what you get is just statistically those people aren't going to be as good because they're over represented in their population basis right. it's and then that creates a negative stereotype around those people and then people just assume that they're there because of this quota. it's just this artistic statistically just not going to happen type of thing.
yeah Okay, so I appreciate the discussion thanks everybody for for sharing some views there. So I think. To me that's interesting. We got into this discussion of. coders and. merit. And affirmative action I guess. From the title of a talk. So I agree, I mean for me, the importance of. equity diversity and inclusion initiatives. is about making. In our case. The population of computer scientists look like. The population in the world around us. And not. Making it so much as. and forcing it but. Recognizing the biases that exist against that. Are the barriers that exist. to having the population of computer scientists. be representative of. Demographics in the world. So. There, maybe. I don't want to say this. gender equity so. apparent, the number of women. In computing. Is is. Much. Different than the number of women to. number of women in society. So there have been many years of. Understand trying to understand why. Women aren't encouraged to take up computer science or computing fields. Where they don't feel welcome.
Is it welcome are interested.
Welcome not interested. A lot of women are interested in studying, but they might not be welcomed into that you.
Are you sure. Because like, if you look at the statistics and universities, women are not signing up for stem.
Well it's not just stem I think. I think other science fields have much better representation I. haven't looked at the numbers for a while, but.
What would make you feel unwelcome in computer science.
I don't know that computer science, especially but. my sister my mom would often tell her that maybe she didn't go for such a hard degree or such a. Few as well now my mom's actually priests access so there's a lot and family members teachers friends. Last small things can put them back in family situations or social situations and things like that can really. drag people down prevent them from getting into. colleges jobs everything like that it's. Teachers can sometimes be racist other students other people in the. job market it's. All a bunch of small things that add up to drag people down over time and I see it, a lot with my sister. But it happens to everyone.
What I think is the main reason women, women don't go in the stem fields is they knew that they know that even if somehow they. managed to get their foot in the door, it is difficult to climb up the the hierarchy in a corporate structure than any. field that they want to, because of the deep rooted Treaty are key and the 50 year old CEOs and their senior managers who might think that women don't have what it takes.
So that's the term patriarchal mindset you in right.
yeah.
I mean tech is one of the most open industries basically on terms of being open minded and and open to new ideas and new people, and so I don't know if that's necessarily.
The basis for. For that statement.
For tech being super open. yeah I mean generally tech is like a younger industry it's not as developed as a lot of other ones um I mean the field is pretty much like the majority of it is 30 years old. And so it's kind of hard to have a 50 year old CEO and the average age of your company is something around 25 or something like that, I believe. i'm not sure the average age of. Computer the computer science industry, but most CEOs and most companies have a super short life form, especially in the startup industry. And, and you don't get that kind of deep rooted hard to climb the corporate ladder type of thing.
Well, I think there's a lot there in those comments that we can think about and discuss. and get more detail but. So what one example comes to mind and. You won't have heard about this. This isn't this is. related. Somewhat tangentially to our discussion here. In the 80s, I live. There were the these sites. Which. we're. which run inhabitable because of chemical. Chemicals left through industrial production, and so one of the. Sorry, one or more of the most. Polluted sites were related to. Integrated circuit manufacturing. So, on the one hand. You think about tech, you know the clean rooms really put together these circuits. as being very clean and. You know we're not dealing with. we're not getting our hands dirty but, in reality, the chemicals that were being used and we're being disposed of in those facilities. Are some of the most dangerous around. So I think. In technology there's an example, there is a tendency to think that. That. That everything's great is doing no harm. That the underlying that may be a. On the surface and when we dig a bit deeper than we see that. It isn't as. pleasant as. We first thought. That makes sense, did I manage to connect those ideas. Anyone.
It makes sense, I understand.
Okay.
So.
I think it's about. So when we're talking about say women in computing. One example is grace hopper. Has anyone heard of grace hopper before.
I haven't. No okay.
She retired she passed away oh I don't I can't remember off hand. But she was behind the development of cobo some of you may not have heard of cobo before. Common business oriented language so is a high level length, one of the first High Level languages. For computer programming. And she was also maybe more famously. associated with. Can. Computer bugs having found a boss in one of the vacuum tubes. ENIAC think that was the name of machine it. At Harvard was it. You can fact check my details here.
feel like mark one.
Okay. So. she's connected to the. phrase computer bug and also. Well, another good one, I think, is. easier to ask forgiveness than get permission. Has anyone heard that phrase before a version of that. yep yeah so that. So those are some other. claims to fame she gave a talk at the University of Regina in November of 1974 when the computer science department here was just starting out. So that was about the year we had some of our first graduates from the Program. Which. we celebrated the department's 50th birthday. We had an event during computer science, education week. Which. computer science, education week is an international. Observance but officially it's from the States and the week is selected to include. grasshoppers birthday. So there's another connection. To grace hopper. She did a appearance on letterman in 19 8085, or so I think that's still on YouTube oh fine i'll see if I can find a link and i'll post it.
Think i'm not a great example of women in computing is Lisa Su.
Su or.
Su Su.
amd.
empty.
yeah.
i'm not immediately familiar with that names that our end okay.
So. Basically, in planning back before 2017 amd is like an afterthought, and so Sue she stepped up as CEO and drove amd too closely compete with Intel and even. Like beat Enzo in a couple of like pockets and such. Look at him the stock price, you see, like a huge bump since 2017.
i'm professor, just like to as like a lot of the, for example, a lot of the things that hunter cited where. they're not necessarily systemic. issues, I mean most if not all, of like the policy related things that kept certain groups of people from being able to join a certain workforce are pretty much illegal. I can't really think of a single.
Legal doesn't mean it doesn't happen.
Right so you're saying that it's basically people's mindsets that are preventing certain minorities from joining certain workforces.
Right definitely yeah definitely.
So I. I don't really see how putting a policy in have a quota would necessarily help change people's mind.
yeah that's what I said yeah.
hey so let's be careful about. quarters. Because I think that has.
negative connotations.
Well, even like having let's say. A program in place to encourage certain groups of people to join a certain industry right The problem here is changing people's minds, which just takes time, I mean even like hunter said his mom might be sexist right but he's not necessarily sexist and that just comes with time.
yeah.
So.
Part of it is acknowledging. The current situation, to say that. There aren't any problems with the way things are present. and say, well, we don't need to fix anything we need to focus on marriage. And marriage. is often defined or has often been defined by people. who have received the most privilege in the system. So Caucasian males. represented. disproportionately I would say, and now i'm not. Let me make that less definitive I am going to guess that Caucasian males are. often placed in positions where. They can evaluate merit. They have a louder voice and talking about evaluating merit. So. I think the opportunity. is to invite more people. To consider these fields. So that. We have. The population of students studying computer science. getting more representative of. The population in Canada, for example.
What if the demographic of the people of Canada aren't interested in computer science.
well.
I feel like saying that is kind of like me collecting, from the point.
what's the point, then, but i'm missing.
That. i'm not sure sometimes the demographic might not support it, but even looking and seeing that there is another person who's off your skin color who's your gender who else. Who is part of the LGBT community makes you think Okay, yes, I am not alone and that there are people that we are still making progress. And we aren't just stuck in the fact that his life to his ability, as well as women's visibility matters in stem because the amount of shift that my sister faces on a daily basis as a computer scientist is no joke.
I mean, people should find different ways to identify with other people rather than skin color. mean can you.
bring up some examples. Maybe.
You should. read it and defining ourselves with our jobs are our skin colors or anything at all, we are all human they take clay, why do it individually ourselves with our work, or why have that perception right.
Exactly exactly but people who interview a sentence did not think that right they don't think that we're all.
of us have you been.
asking me.
Because you're talking about yeah.
yeah because this bias that's known. But a legitimate fox based on this.
Could you say any of those.
I know my my and talk often talk about well, I was doing the pro core program this semester, and I asked my aunt who works in a company. For. advice for interviewing and she would tell me a bunch of stories of. Well, she actually works as an interviewer at your company, a lot of the time so she told me last stories about summer co workers were. slate discovery in often small ways, but. Large ways as well and. it's. Never, how do I put this it's. it's called was the word silent racism it's they just people sometimes just don't think. Well they're racist they don't think that someone who has an accent or different skin color is can do as good a job, as someone who was the same as them it's. doesn't have to be a. Massive and they might might not think they're capable, but they just think someone more like them will be better and so they'll pass up opportunities for someone else it's. I use the word systemic racism before and I was kind of used it wrong it's not the system it's just. there's enough people who work in these industries and who are the either employers or interviewers and they just have preconceived notions that. block or hold back other people from getting jobs or opportunities that other people. Such as white males would normally have easy access to.
You know okay.
So.
i'm not not trying to discourage any conversation about this, and maybe we can. continue this. Well i'm not trying to put an end to it, but I just want to get to a couple other things today. So one thing. One thing that struck me when I looked at Lisa Sue. And I think you can see my screen. is being shared.
You betcha.
yeah so people also asked is Lisa soon good seo. Is LUSA Sue a boy. What is loose the Su salary Lisa Sue a doctor.
I don't think we can see any of those questions, but we can just see the Google page.
If you look down halfway through his pages.
Malta all. The people i'm sorry.
No worries no worries.
So. Well okay. i'm not going to follow the links there. But it's interesting the kind of conversation that happens on Google. Google search. and I wanted to show a couple of links for Google search. Based on yesterday's discussion about controversial topics. So let me go ahead and. Look at that first or. Look at those as well. But before we get to the end of our time, so we can have some discussion about this, so the project proposal. I said to be do at men on Monday at midnight, or one minute before midnight. And I said originally that. We can make that be. The 18th so a week from tomorrow, just before the break. If you want to do that. So i'm open to to making that change to the project proposal. due date.
wasn't in originally after the break.
No, the blog entry was. After the.
Mobile.
So the project proposal is to on a thing now or 14. i'm.
i'm willing to make it.
I definitely want to create a team.
Anyone. opposed to the team.
i'm good with the team.
I just started easier to. I think i've logged in here.
Okay.
Good.
I will make that change right now. So our discussion today that might be. The basis for an interesting project for some. For some people. Okay. So I don't know why again blue on the Gray background it's very hard to read. This do February 18. And while I have everyone here. I want to show you. In the discussion forum. I have a post. or i'm encouraging you to tell me your group before you submit. So that just make it easier for marking. For dividing up. Projects so. The way I did it originally so that everyone belongs to the project group was to put everybody into their own group. So. When I. When I first created project groups everybody was by themselves so. You can absolutely do the project on your own. But you so you'll be in your project group by yourself. So the project groups are mechanism, the new our courses, so that we can treat. All the projects. The same way, whether they're done by individuals or in small groups. So if you can, if you're going to work in a group, if you can. send me a reply to this. And you just need to say. The email addresses and you don't need to put the at your vagina.ca. Just the ID the proceeds the outside.
Anyone everyone in that group needs to reply or only one person is.
Just just one person. we're clock can needs to reply.
All right.
So what i'll do then. What I or the markers will do is then the people who are indicated being in a group. So instead of everybody, having their own groups i'll put will put them into one group. And then remove the other ones. So if you have students in groups ABC and D. And they want to work together. Then i'll put all for students in group a and then remove groups B, C and D. So that makes sense.
yep.
yep that makes up.
So if you can do it before.
You submit.
The just. serve. I think make things run a bit more smoothly. But failing that, just make sure you indicate your group members on your proposal document. Okay.
Do the students will do the project individually have to reply to this form or no.
No, so if you're doing it individually you're. You don't need to reply. it's just if you want to work with somebody i'm encouraging you to. indicate that sooner so. it's just so. What I. It will be easier to distribute to allocate. Proposals for marketing. If I if we have the group's. Set up correctly before we do the allocation. Because there's two markers and if for students are working together, and the way the allocate marks. or work for marking. To the students get in are assigned to one marker and the other two are assigned to the other marker. Then. there's another layer of communication that has to happen. So better if. Before there's your sign for marking. I know what your project groups are, and then I can just assign.
Was it for people who, by the way.
up to four i'm don't have. You don't have to have for.
Just just double checking Thank you okay.
yeah you're welcome. Okay, so change the date on my website as well. So. Going back to our discussion about. Google search so. At the bottom of the search results there's a link to how search works. And Google says their mission is to organize the world's information and make it universally accessible and useful. GU used to say, they would do no evil, but they've dropped that. That was a long time ago. So they described their approach. again. Let me just. Look at. The headings here over the years, the web and world have changed Google search has evolved and improved, but our approach remains the same. continuously map the web and other sources to connect you to the most relevant helpful information. So the question is. Who gets to decide what's the most relevant and helpful information. We present results in a variety of ways, based on what's most helpful for the type of information you're looking for. Again, so there's the idea of most helpful and. Evaluating that or operationalize using what that means. All the while keeping your personal information, private and secure. So they have a movie. Which is not short. trillions of questions, no easy answers. Okay, and then they have different. I think these are different blog posts. or articles. I think it was under features. I had the link, on the other, page and. just go back there. So our featured snippets are chosen. snippets come from web search listings and google's algorithms determine. Whether patrons make a good featured snippet to highlight for a specific search request. Your feedback helps us to improve our search algorithms and the quality of search results. And then. here's the policy for featured snippets. To ensure featured snippets are helpful experience for everyone, you have systems in place to prevent showing those that are in violation of Google search. Google searches overall policies or these policies for search features. So, then, the number of specific. categories which. Specific. To specific policies, so if it's dangerous content deceptive practices harassing content a full content manipulated media medical content sexually explicit content terrorist content, violence and Gore vulgar language and profanity. features snippets also have. I would say that should be have. Since that's plural. featured snippets have this additional features specific policies applicable contradicting consensus on public interest topics. featured snippets of a public interest content, including many civic medical scientific and historical issues should not contradict well established or expert consensus support. These policies, not only apply these pardon me these policies only apply to what can appear as a search as a featured snippet they didn't apply to web search listings because those to be removed. So. That seemed like. We anyone comforted by. The policies. Is articulated here. Any any feelings about that as.
Well, I don't think I could design a more ethical search snippet. thing.
Okay.
well.
So, so I think the issue is. If they certainly say the right things, but the question is how do they implement them. that's my question anyway.
Can I make a quick comment.
sure.
So it's not exactly related, but it is kind of. way back in the like the presidential election 2020. During the democratic primaries when there's candidate named tulsi gathered and she became the number one searched person on Google. When they had their one debate and Google deleted her from searches and you could not find her you'd have to go through several pages to find something about her when searching up her name after that debate.
huh i'm. I remember the name but I don't remember that incident.
yeah I remember hearing about her being like the number one search candidate, but I don't remember hearing about the video obviously because they they removed it from search wouldn't have heard about.
So we're talking about medical content so let's see what. So the rule for medical content is we don't allow content that contradicts or runs contrary to scientific or medical consensus and evidence based best practices. So, again that's a good statement. yeah.
I believe, with a tootsie gabbert situation, it was they suspended her ad account because she said something that Google didn't like I don't believe it was through her Google searches.
will have to do bit more. i'll look into that. For next meeting.
button to articles on it on posted.
Okay. Okay. Okay, so let me go back to. So there's also a link to overall content policies for Google search. These policies apply to content surface anywhere within Google search, which includes web results were results or web pages images videos news content or other material that Google finds from across the web. child exploitation imagery material highly personal information spam. webmaster and site owner requests. and legal requests so. We get back to the same. list here. So there's the. there's the snippet that I showed about. minimizing risks of contracting and transmitting coven. desert. sent me. Medical content. guideline or the. Or the contradiction consensus on public interest topics. Here, let me see if I can do a. Quick poll here.
As we.
get ready to go on our way here. I did that quite quickly here so i'll try again. There we go, so you can. answer that on your way out. And we thank you for today.
Well, on that note, have a good weekend.
thanks you too. Take care.
You as well.
is to have some. upbeat music to play us out for the weekend. Okay, take care, everyone see you on Tuesday. and proposal is due on Friday next week so. spread the word. Okay.
thanks again for Professor a couple of questions would I people to wait until one left after class pesky.
sure.
about the reading that you asked us to do for from blown to bits like. Are we just supposed to like read through the chapter just for our personal reference or something.
well. I didn't expect the longest the discussion that we had. About EPI. My intent is. is to tie in some of the things. That i'm asking you about. it's not just. To make you read things. For your own benefit, I mean I think it's a nice book. So I will try harder to make more solid connections with with material that I asked you to look at. Okay.
yeah so so I was looking into the chapter like I just started off reading the chapter, but like I was kind of confused about like how much of the details are we supposed to remember, or like stuff like that, because, like.
So. What I want to say. i'd like to say something like. The things that we talked about in class. And we reference in class and discuss in class are the things. That we that we will. The foundation for our evaluation, like the final exam and so forth. Okay, so. So i'm not give you a specific answer to say that we should focus on. Section one or.
I just have a question regarding to the blog, is it possible, if you can extend the date sense if you extend the date for the project proposal they'll be like, and so, probably, you know be like will have 10 days to work on the blog entry yeah.
we'll talk about the date for the blog entry next time okay.
Okay, thank you have a good weekend.
But i'm not opposed to it.
really appreciate you Thank you you're welcome.
So Mohammed. So I don't have a specific answer for you, but the chapter four chapter.
I see.
so well.
Yes.
So. The connections, you can make. As you look at. That reference that resource book. And look at other things in the web, think about how they connect to our discussions.
That make sense yeah because I mean look first of all like, as I was reading through the chapter like for us. Most of the parts are just talking about like how, in the previous times how. stops were connected and how Internet was used for like now in the classes we're mostly discussing about how modern Internet or like how Google searches are working, you know, like stuff like that the ethical part so yeah I just got kind of confused so yeah.
OK so anyway, like I said i'll. Work on making stronger connections with. The resource material I indicate to you to look at okay.
Thank you so much, I hope you have a good rest of the day yeah.
shoot to see.
You bye.
bye.
On search, so I guess. Maybe.
yeah I was gonna say to have officers attendance.
Oh it's a 10 okay. I can join the. zoom call there if it's a. it's better.
We are you comfortable just talking now or.
I am yeah um so I just had a couple of questions on the proposal because I was a little confused arm, so our topic it just has to be related to computer science or. Because I was like reading the project proposal on on your website and it's. Like it says here that there's a list of topics, but then you could choose a topic that's new to you do we have to choose from that like list of learning outcomes.
well. So, so the list come from 2013 so they're in the process of being updated by the. by the Association for computing machinery.
Right and when. It goes for four page so.
Oh well. No one told me that. I had fixed. Any links and I son. So.
Because i'm still because there's i'm like does it have to be a research paper or book review or could it be like a YouTube video.
Know it's there's a number of options there. And given a bit of detail about a book review.
Okay um.
And so picture yourself as a competing professional. So the idea of. Discussing. Your roadmap some role models for you as. As you can into computing it's another one, I said, you could write some code. there's a number of different options there.
So i'm one of the topics my partner we're talking about was. The Pegasus spyware some done by a company in Israel. And then we're going to talk about the ethics of our governments, by not kind of spyware and using it basically with taxpayer dollars, whether or not they should be allowed to or whether or not should be illegal, like that kind of thing is that a topic that would work for this project.
sure.
Okay. Okay um. And so doing that in let's say a form of. Of a podcast or video would be fine as well. yeah okay good ah, I just wanted to make sure before we typed up the proposal and that kind of thing. So I appreciate appreciate it.
Oh you're very welcome.
Have a good rest of your day.
thanks you too. Take care.
Professor.
yeah.
yeah it's a non purpose or actually I received the mail from conan week regarding the six sections which and. She told me that, like if it's Okay, for you like if the Professor accepts like then like we thought officially changing the subject, and that should be fine like she told the gift Professor is okay, with it, then that should be fine that was me.
yeah so that's what I was indicating to you as well. And not so many words. So. The only. The only issue is about how the exam. will be given. But. So. we'll have that conversation in the next well. I would say in March will discuss those issues.
Oh yeah sure Professor.
Okay.
So thank you so much.
yeah you're welcome.
Take care.
anyone else left she still wants to talk to me.

Zoom Chat Transcript

Good Morning
Good morning!!!
Good morning
gm
Good Morning
Today weather seems really good
this kind of winer has happened many times in the past and it wont be the last time
winter*
but why have the games in a place that doesn't have snow, that's why people call winter Olympics wasteful
look up how much water the fashion industry wastes every year
vv8t46
Student password
I know last time we were talking about pushing the project proposal due date back. Can we do that still?
Wasn’t it going to be Friday of that week or something?
Yep
yes
Yes
yes
yes
https://www.eventbrite.com/e/the-importance-of-queer-visibility-of-stem-tickets-252362602337
whats the meeting password?
vv8t46
yes
nobody is born racist, its only learned through time
very true. I feel as long as interviews are handled by humans there will always be bias(racism). If the interview process can be streamlined by an artificial intelligence or something similar, then there may be equality.
An artificial intelligence is as good as the person who wrote it.
That also depends on the algorithm though. AI could still produce many issues
For a merit based system, whose standard of merit should be tolerated?? Because people have different levels of education from different institutions.
^
but even then it depends how the ai is programmed and they are programmed y humans
In my view it is humans that change the way of thinking and not an AI machine. It all starts with us
^^
https://www.youtube.com/watch?v=EvDrHUQH1UE
The 18th please
The 18th would be nice
The 18th please
I'd be very welcoming to that change
I don't mind 18th.
sounds good to me
I'm good with the 18th
18th works better
18th Please
wait sorry what’s on the 18th? i went to get some water
project proposal due date
so the blog entry will still be due on 28th
thank you
https://sciencepolicyreview.org/2020/08/reducing-gender-bias-in-stem/
Can we choose our own group?
Yes you can
whats the discord link for this course?
no discord?
https://brookfieldinstitute.ca/wp-content/uploads/FINAL-Tech-Workers-ONLINE.pdf
discord link: https://discord.gg/kZVpsGw
https://bit.ly/3oDIBiX
thank you
gotchu
Group 10 wanna communicate on discord for the wiki today?
sure
yup
sure
yea
after she kneecapped kamala
lol
https://thehill.com/policy/technology/454746-tulsi-gabbard-sues-google-over-censorship-claims
https://techcrunch.com/2020/03/04/tulsi-gabbard-google-free-speech-lawsuit/
I think it meets the guidelines for their snippets but it does leave out the vaccine part which isn't very good
LUL
kekw
loooool
okay....
looool
oh my goddd!! LOLL
have a good weekend everybody
Have a good weekend
Have a great weekend!
have a good weekend!
Thank you
Thank you
Have a nice weekend

Responses

The most important thing that I encountered:

the most important thing that I learned is that how women have the fear of pursuing a degree into STEM due to others questioning their abilities
The different opinions on diversity quotas and how people perceive them.
the guidelines of googles snippets were very direct, however, we are left to google's moral compass in what is right and wrong as they remove some topics from being searched about and also remove apps or search results if asked by a goverment to
The most important thing that I learned in the lecture today is how Google's featured snippets works, how they are selected and the policies around them. Its important to know how you are getting the results for what you are searching.
Google doesn't show false information in search results
I learned that people do not like to hear opposing viewpoints to their held beliefs.
Is that you can see how a search engine tries to give you the best results based on your experience with it
About the discrimination that happens within the tech field as the ratio of men and women have vast difference and also women are being questioned on their abilities and skills.
In today's class we discuss about Class Gender Quality and we go through some great examples like Grace Hopper who put contribution in making COBOL, Lisa Su is CEO of Advanced Micro Devices. We also discuss about Jordan Peterson video in that he mention that women and men are different in two things one is biological and second is cultural.
gogle
Today I learned that many women don't feel welcome in computer science. This was news to me as no one I am exposed to is very sexist and so I fundamentally don't understand why a woman would consider herself incapable of doing computer science because of her gender. We discussed that this idea is often implanted in them by society and hypothesized that that explains why only 20% of the computer science workforce is female. We discussed methods of increasing representation of women such as hiring practice
Everyone is equal. Women also can make a great contribution in STEM. One of the representative is Grace Hopper (women in Computer Science). Behind the development of COBOL, she is one of the earliest standardized computer languages, and also created the first compiler.
The riveting topic of discussion in today’s meeting was related to women and LGBTQ representation in STEM. I think that we must not forget why the quotas were implemented in the first place. These communities have not been encouraged to participate in STEM because of the orthodox rigid mindset of people in charge and the fact that they won’t be provided the equal opportunities to advance their career based on their identity. Blind screening and interviewing process based on merit is a better option.
Today we learned who decides what information is important to us to find on google. Prof walked us through how google handles its snippets. Google's algorithms are the actual gatekeepers of information that decide which information is important to show up on google searches and which one is not. There are certain policies of google that have to be fulfilled for information to be uploaded there for people to view.
Google snippets are like previews of the website. They often show short information about what you've searched. In addition, when you click on the google snippet's link, it will often jump to the previewed information and it will be highlighted. Moreover, snippets will help people find what they are seeking.
Society has changed a lot since it started and we need to change with it
The most important thing that I learned is that there is discourse about if inclusivity programs are helping or hurting the groups of people and work places. It helps individuals get entry to jobs they may not have been able to get otherwise but does this cause the individual to be more discriminated against in the workplace as people feel they have been given an unfair advantage.
In today's class, I was able to know my friends' thoughts and professors' thoughts on gender equality.
That diversity encouragement programs for companies were created to benefit minority groups to help breakdown the barriers of entry for minorities. However, they can sometimes hurt them due to people questioning whether they were actually qualified for the position, which creates new issues.
Is that there may still exist a gender inequality in workplaces.
The thing I learned today is that a lot of water was used to make the Olympic in Beijing. We discussed about Wikipedia, Google, Lisa SU. Changed project proposal date. We discussed about Stem, equity and diversity.
Today I have learned many things, like how google search engines works, googles featured snippets work, and we had also discussed on many topics like amount of water used to make snow in Beijing for winter Olympics, I was surprised by the answer as it was 49 million gallons. I wasn't aware of Grace Hopper, she was involved in the creation of UNIVAC, the first electronic digital computer and she was also behind the development of COBOL, it was one of the earliest standardized computer language.
I didn't learn this, I already stand by this. Equal rights for all!
Learnt how some certain communities are viewed just because people don't agree or feel the same so they choose to treat them poorly. The importance of google and google search, helping people around the world seeking answers to various questions and just those interested in gaining knowledge for free without the need of living one's home. Learnt about the history of one of the earliest computer languages created by a woman in computer science.
the most important thing I learned today was that the fact that corporations are purposefully looking for visible minorities to hire is in fact encouraging or emphasizing discrimination. it can make others wonder if you were hired because you can do the job or if it was because your part of a marginalized group. I would like to know more about the different ways and methods that are being used to combat this issue, specifically using tech aside from IA.
I learned that biases exist in the population of computer scientists relative to the world demographics. There are policies to help mitigate this gap, also the government tries to create awareness to the presence of the inequality in industries in society. Additionally, I learned how google makes use of snippets. There are policies in place to ensure that snippets meet documented criteria. However, there is no way to verify the level of implementation by google.
Today, we have discussed about the Queer Visibility of STEM. We also discussed about the transparency of google search and like how their featured snippets work. we had a pool about snippet of Google's meeting standard on it or not.
In today lecture we discussed about the huge amount if water used in Beijing Winter Olympics and also discussed about the google snippets and its polices. The main discussion of the class was 'The Importance of Queer Visibility of STEM (Science Technology Engineering Math)' this led to the racial and sexual discrimination at work places. According to some people women's are not treated fairly at work place. This are the somethings which got to learned in todays class.
The most important think I learned is about how google works ..i always wondered how does it comes up with this accurate and relatable results but now I know . Thank you for today’s class sir.
I learn most important thing in today's meeting that amount of water being used in winter Olympics is just to gigantic.I always wondered that why waste this much water when you could actually use that to help those who really need it .
The most important thing i learned today is beijing used large amount of water to make snow for winter olympics. today's important topic was the discussion on STEM(Science Technology Engineering Math) then the important topic was the google search and snippet policies. the important topic was on the LGBTQ equality and diversity. The discussion was on the gender equality as grace hopper had achieved a significant position in computer science by developing cobol. the important discussion was on the project pr
I came across a lot of new ideas today. We talked about Winter Olympics that is happening in Beijing, and how they used a lot of water to make artificial snow. Someone also raised a good point of holding such events at the places where there is natural snow, so in that way we can save a lot of water. We also talked about silent racism that happens almost everywhere. The reasons behind it and various ways to deal with it. I believe that the main cause behind this silent racism is prejudiced mindset.
Visibility of minorities in STEM should be discussed more. Representation and participation in STEM of such minorities and why it should be spoken about more. And while discussing about it, said minorities should be involved in the discussion as well. Learning about people like Lisa Su and Grace Hoper can also encourage minorities.
The most important thing I have learnt today is how google search works and types of features it provides the user to make their work more easier.
Today we discussed abstracts. Abstracts come from snippets of your web content, which are extremely relevant to the search content. The aim is to provide a quick solution for searchers. Currently, the main form of the presentation is text-based, not excluding the possibility of images and short videos, which means that Baidu Featured Abstracts have a significant role in keyword optimization rankings. When you want to learn more about the relevant content, you can access the original text given in the Baidu
i learned about the obstacle for certain groups of people in their way to succeeded in the tech industry.
In the beginning, we discussed the representation of minorities in this field should be based on merits or not. Then we talked about women not choosing the field of computer science is due to its difficulty level or they are not allowed to do so. At last, we compared many search results related to covid with that of Google and had a conversation about that.
In todays meeting we discussed and In my view it is humans that change the way of thinking and not an AI.
In todays meeting we discussed that a large amount of water is used in winter Olympic to make snow in Beijing. And we also discussed about project proposal and also told to inform professor as soon as possible for group members. The professor also told us to watch "Stranger than Fiction Case Studies in Software Engineering Judgement" by Steve McConnell for next meeting.
The important thing I learned today is about stem and how it works and discussions about lack of qualified graduates to work in high tech jobs
Google has an asked questions section that I didn't know about until now.
I loved the concept how google search engine and its snippets works. And hope to learn similar stuff in the future lessons.
In today's class, we discussed about LGBTQ representation on equity, diversity, and inclusion in STEM due to prejudiced minds (silent) racism. We also discussed about the project. Professor has extended the time till Feb 18th. Thanks.
the most important thing that I learned unfortunately is that silent racism and prejudice against minorities still exist in the work field against LGBTQ and women. I also learned that we do have to stand up for the minorities and help them to be equal like other people who are in the work field. I also learned that sexual orientation and race must not be something to judge or to be a qualification on the person who has applied to STEM. We should also encourage women to get involved more in STEM and prohibit
The discussion regarding google searches was pretty interesting to take in, learned a lot of new things.
In general, robotics and AI are tending to present two distinct sides: the traditional side with its masculine face of mathematics, logic, and large, heavy industry, and the other side with its light, gentle humanism and rich human applications, which seem to be the specialty of female researchers. In fact, it's not just women; the field of robotics and artificial intelligence requires a much broader diversity, including culture. Translated with www.DeepL.com/Translator (free version)

The most difficult thing for me to understand:

I struggle to understand why some would prefer a minority/LGBT 'visibility' policy rather than a meritocracy. It feels almost patronizing, as it assumes intervention is necessary to achieve visibility, which is clearly not true.
Why there is so much racial/gender bias in Computing Profession. The gap of male and female computing professionals is quite noteworthy.
Is it possible to design a program that is free from biases? Big part of being more diverse and inclusive when it comes to the hiring process is removing that element of human bias. AI models needs to be built from preexisting data. if their is already precovecied notions in the workplace of bias, how can AI overcome it? Also this AI would have to pinpoint equalitive outcomes to. If there are two equally valued resumes, would it be as biased to pick one based on diversity just because their work lacks it?
Something that is difficult for me to understand is how to best approach intersectionality in our society. Intersectionality is a topic of great debate and I find myself lost in the middle at times. At first, looking at it at face value seemed simple, although after more discussion, I find it clear that is a broad and complex issue. I admit that I am not fully equipped to speak intelligently on this matter, so I have not much in the way of arguments in favor or against methods to enhance equity in society.
As we were talking about the importance of queer visibility in STEM, I agree with most students in the class that prejudiced minds (silent racism) is causing for the government to create policies for inclusion. However, some companies are rather using these policies for the use of representation rather than merit. What I want don't understand is how people can't just have an open mind and release their biases towards certain genders, sexual orientation, or cultures; and just hire accordingly.
Why women don't chose STEM fields? Is it because they don't feel welcome or is it because they are interested? Merit is often defined by people who have received the most success in a company or freedom in a field.

The thing about which I would most like to know more:

I'm not sure how Google can be more or less clear in its efforts to transfer information from a website to a user. It's possible that I'll have to do further research, but I'm not sure what terms to use in my project proposal.
Today we talked about Google Search options, and I would like to more about algorithm and snippets.
I would like to know more about the project and certain topics we can work on, such as examples of real-world topics that would be acceptable for the project that relate to the course.
The discussion between whether the races will influence their chance to get job or not leaves me an impression in today’s class, I think that people should not describes a person by their skin colour, everyone has their own advantages and disadvantages, you can not tell if the people is good in the work by their races.
Why should the public report a snippet? Shouldn't google already have read the snippet and ran it through it's system to determine if it goes against one of their policies?
more representation of women is needed in the tech world
Google's safe search algorithm. Do they manually screen content? If so, do they employ a large number of people to this means? How would they ensure that diversity is met while employing people to prune the results? Similarly, if they use an algorithm, how do they ensure a lack of bias?
One thing about which I would most like to know more about is minority representation in STEM. Is silent racism still a current issue, and how can it be combated. Are diversity quota's a good ethical practice or does it give jobs to less qualified applicants, just for the sake of diversity so the company does not get in trouble. What can be done to prevent discrimination towards immigrants that are applying to jobs, especially fields dominated by the majority race in the country.
In today's discussion we discussed the reason why few women take stem? Do they just lack interest or feel unwelcome? I think it's a bit of both. I think some women doesn't do stem because they are not interested. I think the reason is when they are kids the parents introduce dolls to girls and cars and robots to boys. So boys are more exposed to technology stuff than girls. So I think the lack of exposure to stem is the reason few women take it.
I'd like to know about different perspectives when it comes to encouraging women and minorities to participate in the technology field.
I would like to know more about the women interest in coding as much as men topic. I honestly don't see many women in my coding classes and I was wondering why?
the thing I would most like to know more about would be how often google personally decides to curate their snippets rather than relying on an algorithm to choose them. Certain snippets do not seem to match their own rules so it makes me wonder.
We still have a long way to go in making STEM, and Computer Science especially, to be a more inclusive work place. According to the discussion, people experience many micro-aggressions in the work place. Because these actions are so subtle, the pain it inflicts is hardly noticeable to someone unaware. I want to know more about the kinds of efforts companies are putting in place to make computer science a more welcoming place, and I want to know who are the people we are trusting for implementing them.
I would like to know more about some of the factors contributing to gender inequality particularly in the computer science field. The number of women in computing world is much different than the number of women in the society. There have been many years of trying to understand why women aren’t encouraged to take computing fields/computer science. I would like to try to find an answer for the question "Why women don’t feel welcomed in this field?"
the data on minority status workforce in tech vs other similar industries
It was a good session about STEM, and had some good discussions.
Today's discussion about gender, race bias is really interesting. I want to know more about how to prevent Discrimination. So far, Canada did a good job at preventing it compare to US or other countries. I think the most important factor is diverse education that young generation received
I would like to know more about those polluted sites which were in the 80 i think this was something interesting to learn and know about the past how it used to happen.
With biases present in both humans and algorithms, should people or computers conduct interviews?
who did the most contribution on reducing gender discrimination in STEM
After today's meeting, I found the discussion about women in STEM to be interesting, and insightful hearing the different opinions. Although some were in denial of the environments that create barriers for women joining STEM, the facts remain that women make up only 28% of the workforce, while men dominate the rest. With that being said, it is important to educate the public of the gap, which is where I would like to know more about how the CS community can play a hand in this.
How do we as a society encourage more women to take up STEM careers? It is such a male-dominated industry that really doesn't need to be. I don't believe there are any intrinsic difference between men and women that make men more suited for the industry. So we can we do to help balance it out?

Wiki

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