Hey all. Here’s Digitally Literate, issue #354.
Welcome to 2023! I took some time away for the holiday season and I’m excited to get started on some new initiatives.
I posted the following since we last saw each other:
- Wicked Problems – Many important societal problems are neither simple nor easily solved; they are wicked problems. We should give students opportunities to address wicked problems in classrooms.
- Blending Practices, Skills, and Content in Teaching and Learning – Interdisciplinary is good, transdisciplinary is best. Metadisciplines might be the linkage between the two. All of this is assuming we don’t want to live in our own silos, and we do want to address real-world, wicked problems. (＾▽＾)
- Transdisciplinarity as a Gateway to Critical Literacy – I gave a webinar last week explaining all of this, and providing some insight into the barriers and accelerators.
Over the past month, two big things really caught my eye. The first of which was this announcement of the successful fusion experiment at the Lawrence Livermore National Laboratory (LLNL). Watch the full announcement here.
This is a BIG deal. Don’t take my word for it. Here’s Neal deGrasse Tyson.
The other giant story from the last month is obviously the influx of stories around GPT-3 and ChatGPT. It’s funny that we briefly discussed this here in DL a little over a month ago, and then it caught like wildfire. I’m very excited about this, and looking forward to writing more and folding it into my teaching.
One thing to keep in mind is that the real story is Generative Pre-trained Transformer 3 (GPT-3). This is a machine learning language model that uses deep learning to produce human-like text. GPT-4 is supposedly right around the corner and (I think) it’ll all make this seem so quaint.
Why this matters. ChatGPT is super cool for some and super frightening for others. ChatGPT is one proof of concept for artificial intelligence (AI) and machine learning (ML). It’s not the first and it’s not the last. What matters is what we do with these tools.
As I play with GPT-3 tools, one of my key habits that is changing is my tendency for Internet searches. I’m an Internet researcher. Yet, I’m spending far more time talking (arguing) with text generators trying to get it to give me the info I want.
Previously (last month) I would search something in Google or DuckDuckGo. I would search Reddit, social media, or discussion groups. I’d assemble all of this info in my personal knowledge system. Call me lazy, but the time it takes to scroll through the first page (or two) of Google, along with the ads, bogus links, and other materials seems like a waste of time. Yes…these text generators are pulling from this same vat of info, and may give me the same bad content. But, I’m waiting to see how quickly the generative technology changes, and also thinking about how my skills of looking for credibility, relevance, and sincerity can interact with this bot.
Why this matters. I’m not going to say that Google is dead…but…the parent company (Alphabet) had better make use of their treasure hoard of data they’ve been collecting. For now, check out You.com, the search engine startup founded in 2020 with a moonshot bid to take on Google. They’re opening up to developers and building in generative AI search that has never been seen inside traditional search engines. You can use generative AI technology that enables users to generate text (YouWrite), code (YouCode), or images (YouImagine) from plain English — all within the search results page.
We haven’t talked about Twitter in some time. In the discussions I’ve had, I don’t focus on the climate and culture of the company and/or social media space. I don’t spend time thinking about whether or not you should delete your account. My focus is on the challenges of online content moderation…and the normal rise and fall of companies and networks.
It appears that Meta, the parent company of Facebook, is falling apart. There’s a lot to dig into, but it will be interesting. Elon Musk and his crew may or many not be driving Twitter into the ground.
Why this matters. The end state for Twitter will come at some point, the key question is how can we avoid the harm being done to folks in the process. danah boyd indicates that failure isn’t a state, but it can be a process. It can be a generative process. Sometimes we need to rip the bandage off to let the healing begin.
Monique Judge with a great piece that details a desire to get back to the community-building aspect of the Internet. Judge suggests that we can take the power back by building blogs.
Why this matters. You need to control your own platform and write yourself into existence online. I’ve had several discussions online with folks indicating they’d like to build communities around blogs. What say you? Do you blog? Do you want to have your own place online to create?
I’ve been thinking about a series of monthly blogging challenges to inspire folks to create an connect. Would this be of interest to you?
Brice Ménard, an astronomy professor from Johns Hopkins University has given us the chance to zoom way out in both time and space with an interactive map of the observable universe. The Map of the Observable Universe depicts the position of 200,000 galaxies, using different colors to show how far away they are and how long it has taken for their light to reach a telescope at Apache Point Observatory in New Mexico.
The full map is a sphere, but it’s not possible to show all of its data in a two-dimensional representation. The online map shows a slice of the sphere that’s about 10 degrees wide.
Why this matters. I love playing with open data (Sloan Digital Sky Survey) maps and tools like this. It is an opportunity to gain some perspective while also inspiring ourselves and future generations.
Our brain is wired to try and make of the world and reduce uncertainty. We make up stories (schema) to create a worldview to help us organize and interpret events and information. We generally do not do well when we have to deal with uncertainty.
The Uncertainty Matrix, sometimes called the Rumsfeld Matrix, is a tool that can be used to help make decisions when facing an uncertain situation. The matrix consists of four quadrants: Known-Knowns, Known-Unknowns, Unknown-Knowns, and Unknowns-Unknowns. Each quadrant represents a different type of uncertainty, and each has its own set of possible solutions.