Some freeform blogging. Some bits and pieces, mostly.
I’m currently knee-deep in uni work and assignments.
I used to roll my eyes at RMIT’s Information Management course being part of their School of Business, and the business subjects that were compulsory because of that. So it’s a bit embarrassing to find myself using things I’m learning in my Business Analytics and Knowledge Management classes in my day job.
How to write a literature review… using AI flashcards!
One of my biggest frustrations with uni is constantly thinking “this topic is really interesting – I wish I had time to really learn it properly”. I’m two-thirds the way through a Masters degree and I still don’t understand how to write a proper literature review, let alone how to catalogue an item, or set up a digital repository.
So when I saw a video on how to write a literature review posted to Twitter, I made some time to watch it.
It’s presented by Scholarcy, which is a tool for using AI to parse and summarise research papers.
Again: that sounds really interesting. I wish I had time to learn about it properly. 😁
During the video, a slew of other interesting research tools get mentioned. I’m posting them here because they sound cool. I have most definitely NOT had time to look at them yet:
- Connectedpapers.com shows relationships between academic papers in a visual graph
- Scite.ai lets you check how a paper has been cited, and if it’s findings have been supported or contrasted by others
- Semanticscholar.org applies artificial intelligence to extract the meaning from the scientific literature allowing scholars to navigate research much more efficiently than a traditional search engine
- App.2dsearch.com – lets you search multiple databases using a visual query builder, instead of the traditional Boolean strings
AI in the library
There’s nothing like being busy to stimulate your mind with projects that you don’t have time for. I’ve been procrastinating from uni work by thinking it might be fun to write a summary of the way AI is being used in libraries.
This would be a really interesting project, and I absolutely do not have time for it.
So here’s a scrapbook of some things I’ve read when I should really be reading things for uni:
WHEN YOUR BOSS IS A ROBOT
Amazon doesn’t trust its self-driving cars to do their deliveries, but they’re happy to let their alogrthms schedule and monitor their huamn drivers. Hugh Rundle has annoted his readings on the way algorithms replacing middle management, monitoring workers performance and punishing them if they fall outside the parameters.
STOP CALLING EVERYTHING AI
Current “AI” can do basic pattern recognition, but is a long way from approaching human insight and creativity. This artilce is a profile if Professor Michael I. Jordan, a leading researcher in AI and machine learning at the University of California, Berkeley.
WHY COMPUTERS WON’T MAKE THEMSELVES SMARTER
Science fiction writer Ted Chiang on the logical flaw in thinking that an intelligent machine will be intelligent enough to make itself even more intelligent.
Museum at Home
I attended my first online #CardiPary tonight. The guest presented was Bridget Hanna from Melbourne Museum’s Learning Lab.
She talked about how the new interactive, multimedia Learning Lab opened in February 2020… and then had to close the next month as COVID restrictions came into force.
Rather than letting their educational and programs team go, as some other museums did, the Learning Lab team pivoted to presenting museum material online. This involved providing staff with over 20 sessions of digital literacy training, from video editing and animation to documentary filmmaking and how to present to camera.
The result was the Museum at Home program.
Now that things are reopening, the team is struggling to continue providing events and content both online and onsite. There’s a need for both, but they still only have the same resources and number of staff as before.
You can read my live-tweeting of the event on my Twitter.