Yesterday was the third classroom session of IS101-3003, Spring 2023. Tsz earned the highest score on Bonus Quiz 3 – Jump Ahead & Special Characters in File Name. I am proud of the young man from Hong Kong ^_^
After walking through the results of BQ3, threaded discussion (TD)03 Unique Topic from 1.5.7/Sources Comparison, TD04 Email Inbox Rule(s), Blog Checkpoint, and How to correctly interpret your scores & progress in Canvas and completion in LabSim, I concluded the class session with the first of series lectures: L1 Hardware, Troubleshoot, End-User Cyber Security.
As BQ03 enticed students to jump ahead to read about A3 Tailored Cover Letter and Resume, the PowerPoint version of my L1 gave students a glimpse into A5 Slideshow Presentation, and the webpage version of my L1 not only contains focused reiteration of some key points that will help students with next Saturday's BQ4 Display, Shift/Ctrl, Boot-up, Binary, IPOS, but also contains a link to one of the five sample homepages I created to help students conceptualizing and designing their own homepage for A4 Homepage, Website, Online Publishing. One requirement for designing A4's homepage is the use of a table or tables to align contents instead of using tabs, spaces, or other means from Microsoft Word that do not translate to a webpage. My students will learn about tables in Microsoft Word in a few weeks.
L1 Hardware, Troubleshoot, End-User Cyber Security
L1 Hardware, Troubleshoot, End-User Cyber Security (Tables' Borders Visible)
The fourteen students are occupying the full range on the progress spectrum. Majority are keeping up the semester timetable with a few working ahead and a few falling behind. I hope more will join the frontrunners and the few that are behind the curve will resolve the challenges in their life and catch-up.
Continuing from the last week's video of Artificial Intelligence (AI), here is a video on one area where AI plays an integral role: Facial Recognition: Last Week Tonight with John Oliver (HBO). The video may be from two years ago and the topic is at least a several years old but the implications are just beginning to be vetted.
Note 1: Viewer discretion is advised as the 21-min video contains strong languages and John Oliver's brand of humor. If you are under the age of 18 and cannot obtain your parent's permission, let me know and I will give you an alternate assignment in place of watching this video.
Note 2: When I tried to search for this video through Blogger's YouTube video search/insert function, Blogger (owned by Google) would not return it -- along with almost all of John Oliver's videos -- as a search result. Hence, I inserted a screen capture of his video and pointed you to the URL. If that doesn't work, visit https://youtube.com and search for this video.
The five statements that stood out for me are:
(1) Driver license photos from residents of these states (including Nevada)
(2) 'Skynet but good'
(3) Only 8 out of 42 matches were verifiably correct
(4) "...argues that it has a First Amendment right to harvest data from social media."
(5) "...'unconventional databases' for 'extreme opposition research'..."
These funny lines stood out for me as well: 'loser fish', 'your brain autocompleted the rest', and 'accidentally made tennis interesting for a day'.
Students, please share your professional thoughts on what you learned from his video in your comment to this blog post :-)
I had no idea that there is a "search engine for faces", or that "you're in that database even if you don't know it". Clearview.ai harvesting data from our social media seem to be in my opinion a violation of sort to privacy. I do like that Illinois has a law that requires written permission before collecting a person's fingerprints, facial scans or other identifying biological characteristics. They should prohibit private sectors and institution from collecting biometrics data from unaware people either in the state or online. And I do not agree with Hoan Ton-That statement when he said "the choice now is not between no facial recognition or facial recognition, it's about 'bad facial recognition and responsible facial recognition' and we want to be on the responsible one". I understand about mug shot being used by law enforcement to find repeat offenders but what really is a 'responsible facial recognition'? It all comes down to being 'ethical' doesn't it?
ReplyDeleteAll of this technology and uses around facial recognition terrifies me. It worry for my kids generation and where this technology and others like it will be when he is an adult. This is partially why we won't allow him to have certain social media accounts and put his face out there. Already in certain places they scan your ID and not just the back of the ID the front for certain purchases. Hmm☠️
ReplyDeleteThe problem I see with artificial intelligence recognizing faces is the same problem I have with artificial intelligence in general... who has control over it? Just as this technology can be used to track down criminals, it can be used just as maliciously against law abiding citizens. Though there is benefit in this technology, the cons far outweigh the pros in my eyes.
ReplyDeleteTo me this sounds like the data sets used to train the AI (ML and DL) were not refined nearly enough. I'm definitely glad I'm studying this field, seems like I'll find employment :)
ReplyDeleteThe technology surrounding facial recognition has been around for years but it wasn't until recent years the science behind it became more sophisticated and advanced; software applications capable of using facial recognition as a procedure of authentication and verifying people's identity grew tremendously. Law enforcements have also utilized facial recognition in ways that would be deemed controversial by many and an example was the use of facial recognition in Black Lives Matter protests to scan protesters faces, find more information about their background and initiate arrests for those who have arrest warrants. Since the introduction of facial recognition software many countries such as the U.K, Australia and China have began articulating and endorsing this technology. Databases such as "The Capability", "Clearview.ai", "Skynet" are a few examples of facial recognition softwares that have been recently introduced and they are able to gather data by searching through people's social media accounts and footage from video surveillances.
ReplyDeleteFacial recognition is everywhere and like mentioned in the video our faces are most likely already in the database. This happens when we post pictures to any social media network. Facial recognition can be used for good purposes, but it may also be used as for bad. An instance is a bad intentioned individual using facial recognition to find out who a person is. Facial recognition errors are only bound to happen. The algorithm isn't perfect and often doesn't identify the correct person.
ReplyDeleteI haven't seen anyone comment this but... our phones have our faces already in a database! I use an iPhone, and more importantly, I use face ID in order to gain access to my phone. What does that mean? Apple definitely has my face stored in their database, but because of this, I know that whatever secrets I hide in my phone are SAFE.
ReplyDeleteWhat an insightful video! I learned of the issues surrounding facial recognition technology, including its potential for abuse by law enforcement, its lack of accuracy, and its invasion of privacy.
ReplyDeleteMost importantly, John Oliver emphasizes the need for increased regulation and oversight of facial recognition technology. It is essential to ensure that the technology is used ethically and responsibly and that the privacy rights of individuals are protected. The video serves as a reminder that technology is not NEUTRAL and that its development should be guided by ethical principles that prioritize the well-being of individuals and society as a whole.
Face recognition is a two edged sword. We should enforce the law on face recognition in order to protect the safety and privacy of people. Apart from the bad side, there are also advantageous on face recognition and government should make use of it to do correct things.
ReplyDeleteAs the video said, face recognition can distinguish between winner fish and loser fish. Maybe, it could also be distinguish between winner pet and loser pet. World Society for the Protection of Animals could file a face recognition law and check the pets on sale whether they are loser or winner. If they found that a lot of loser pets in a store, it is very likely that those animals are from puppy mill.
Only 8 out of 42 matches were verifiably correct? Wow. I am trying to play around with ChatGPT but I haven't been able to have much success of creating what I really want. The people in the YouTube seem to make it so easy looking but it hasn't been.
ReplyDeleteI knew pretty everything the video was trying to talk about. It's even worse when it comes to law enforcement and the amount of surveillance they can achieve. One good example is WAMI or Wide-area motion imagery. This technology employs specialized software and a powerful camera system—usually airborne, and for extended periods of time—to detect and track hundreds of people and vehicles moving out in the open, over a city-sized area, kilometers in diameter. WAMI systems usually have a 0.5 meter ground sample distance (GSD)—enough to detect and track moving targets throughout the scene. Should a user need to take a closer look at a subject, the WAMI system can cue other available sensors, such as hi-res full-motion video cameras, to make the identification. Users can select different video streams pulled from the WAMI system's vast field of view and, with the help of advanced data compression techniques, watch them live on their computer screens or handheld devices. In some systems, users can also designate "watchboxes" within the sensor's field of view to provide automated alerts should the system detect movement in the area. Here is an example of WAMI: https://www.youtube.com/watch?v=lDIkeqf9tMA
ReplyDelete