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Artificial Intelligence & Libraries: Prepare Yourself

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A huge thank you to Lise Brin. Program Officer / Agente de programme @ Canadian Association of Research Libraries/Association des bibliothèques de recherche du Canada for compiling this list of pertinent, thought-jarring items on #artificialintelligence and the implication for #libraries. We’ll be discussing this @ CFLA-FCAB’s National Forum, May 2nd in Regina (co-located with Sasktachewan’s Library Conference). Read, reflect, and ready yourself to provide input and inform the CFLA-FCAB Board for positioning libraries in the age of #AI.

TheConversation.com

1 How can Indigenous knowledge shape our view of AI? (Karina Kesserwan, Policy Options, February 16, 2018)

 

2. Bias already exists in search engine results, and it’s only going to get worse (J. Snow, MIT Technology Review, February 26, 2018)

3. Here’s how Canada can be a global leader in ethical AI (F. McKelvie & A. Gupta, The Conversation, February 22, 2018)

 

4. Libraries in the Age of Artificial Intelligence (Ben Johnson, Information Today, January 2018)

5. Artificial intelligence and the library of the future, revisited (Catherine Nicole Coleman, Stanford Libraries Digital Library Blog, November 3, 2017)

6. The Seven Deadly Sins of AI Predictions (Rodney Brooks, MIT Technology Review, October 6, 2017)

7. Who Trained Your A.I.? (April Glazer, Slate, October 2017)

 

8. The AI-Enhanced Library (Norman Jacknis, Medium, June 21, 2017)

9. How libraries might change when AI, Machine learning, open data, block chain & other technologies are the norm (Aaron Tan, April 9, 2017)

10. What happens to libraries and librarians when machines can

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Ethical AI: What Will That Look Like for Libraries?

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At a January 2018 Girl Geeks Toronto event on Ethical AI, we listened to 3 articulate, brilliant women discuss the engineering feats and ethical vulnerabilities of current and near-future artificial intelligence. The recording is very high-quality, and I encourage you to grab a hot beverage and watch it – and listen. Listen very carefully. Inmar Givoni (Autonomy Engineering Manager at Uber Advanced Technologies Group), Karen Bennet (VP Engineering at Cerebri AI) and Anna Goldenberg (Member of the Vector Institute, Assistant Professor at the University of Toronto Department of Computer Science, and Scientist at the Genetics and Genome Biology Lab at SickKids Research Institute), each focus on different areas of engineering and may not share common experiences or opinions. But one thing they do agree on is that it is a problem that ethical and societal policies regarding AI are not keeping pace with the technologies. Not keeping pace! These policies aren’t even in place in Canada. There’s no point in pointing fingers or wringing hands; we need to grasp hands and join in leading the way.

It’s no secret that I am intrigued and concerned about the impact of artificial intelligence on public and academic libraries. It’s one of the reasons I’m involved in planning CFLA-FCAB’s first National Forum in Regina on May 2, 2018. Whether you agree that AI will bring significant shifts to the library landscape, you no doubt think about the shifts AI is and will bring to your communities, your life and our campuses and

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Artificial Intelligence: AI - All In @ #CFLAFCAB2018

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Save the date! May 2, 2018 – CFLA-FCAB’s First National Forum @ Saskatchewan’s Libraries Conference! Be a part of history – be a part of informing Canada’s library policies on Intellectual Freedom & Artificial Intelligence. #cflafcab2018

Why #ArtificialIntelligence? #AI stands to impact all parts of our lives, our work, our communities and our education. And since libraries – whether they are in the public, academic, government, school or corporate sectors – are an integral part of people’s lives, work, community and learning – AI is a significant issue with which we in the information and library sector must be involved. We can’t just be impacted by AI. We must use AI.

AI is all about data. Libraries have data. Lots of data. Are we using it? Mining it? Gaining deep insights from it? Using it to build AI tools? C’mon – admit it. We may be using our data in traditional ways, such as for operational decisions or reporting, but we are not mining our data to identify patterns and use for decision-making.

MIT Massachusetts Institute of Technology’s magazine lists the Top 10 Breakthroughs expected for 2018. While all 10 have a ripple effect for libraries, 3 have

significant implications for information-intensive services and work:

Sensing City (see below) AI for Everybody Perfect Online Privacy

Let’s take, for instance, Sensing City. Given that I’m sitting just north of Toronto, and given that Toronto is the city used in the example, this seems reasonable. Quoting from the zine:

“Numerous smart-city

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