Sophia, AI and the importance of curation: KIM is safe (for the time being)!

I’m lucky. I get to travel to some of the most interesting places on the planet and experience different cultures. These last few weeks for example I’ve been on a book / Masterclass / conference trip to Hong Kong, Kuala Lumpur and SIngapore.

Book launch hosted by Petronas KL

More on the issues that arose around KIM accreditation and the outcomes from KM Asia in separate blogs.

Over dinner in Hong Kong I got to talk about “Sophia” the locally based Hanson Robotics model that controversially has been given citizenship of Saudi Arabia. While hugely impressive and a major advance in sensory technology two quotes about Sophia stuck with me:

Why are we humans obsessed with creating life forms in our own image?” and

“Dogs are able to sense what their master’s mood is. Imagine if we could replicate that in Sophia?”

“Km has gone thru peak of inflated expectations which AI is now going thru”

This was one of KM Asia’s Day Two Chair Les Hales opening remarks.

It’s a good backdrop to focus on the ever increasing clamour I sense around the use of AI / machine learning technology to improve effiiciency and outcomes, reduce headcount +/or free up time for more added value work. In the Masterclasses and presentations I suggested AI is addressing 3 questions on expertise, transactions / news and process:

I noted there has been a lot more in the way of measurable progress on transactions / news and process enhancement than on expertise. In his presentation at KM Asia, Eric Chan of Hutchinson Global Communications showed examples of a couple of regionally based organisations who now used Chat Bots

His examples above which focused on the process question confirmed the widely held assumption that many industries are ripe for disintermediation by AI technology. I noted a couple of his comments:

“Replacing customer service agents by chatbots powered by AI. Achieves 9/10 satisfaction and not subject to selective memory and

1/3rd of work can be done by machines = disruptive stress”

What was really interesting about the Chatbot example? How the difficult customers (the ones who shout) get routed thru to a human!

So where does this leave Knowledge & Information Management? Actually not badly if Eric Hunter’s comment is to be believed:

“The rise of newer forms of technology is challenging the way codified knowledge is managed leading to the need for KM professionals to work with new types of colleagues such as business process improvement specialists and AI providers.”

Note the use of the phrase to work with not be replaced by. Here’s why I believe this to be the case.

The importance of Curation (…ate #7)

One of many positives to emerge from every stop on my Asian adventure was a reaffirmation of the importance of curation, a term Patricia Eng and I described in our book thus:

#7 Curate: So much of what passes for Knowledge Management is about creating and storing content and making it available for reuse. It’s more than the role formerly undertaken by Information Professionals and Librarians, here we are talking about being a custodian of organisational knowledge and organisational knowledge bases.

Technology has for some time been knocking at this door.  Indeed companies like Profinda have made significant strides so it was fascinating to read this very well written piece on Microsoft’s evolving Yammer strategy by Antony Cousins, Director of Customer Success which reflects my ongoing concern that Technology is not Knowledge Management:

Lost knowledge. With the same room structure as Yammer, there will be popular generic rooms where far too much is shared, too little is relevant to users and, should they ever want to find that document or that chat thread which was relevant to them, good luck. It’s lost in the never ending deluge of chat never to be seen again. If we can’t easily find previous answers and solutions or reference points, we’ll be as doomed on Microsoft Teams, as we were on Yammer, to ask the same questions over and over or worse, repeat the same mistakes…. So, in general, well done Microsoft for making things that were quite easy about 6% easier. Now can we please focus on the really big problems still faced by those of us trying to resolve the collaboration problem for big business?

I continue to argue that one of the key aspects of the role of KIM’ers is acting as Curators of organisational knowledge as well as signposts / navigators. In fact this was the premise behind my Masterclasses in Singapore and Kuala Lumpur and the need for those skills:

KIM’ers have to be good at understanding technology and its implications for the business. But they are one of the few groups organisationally who see across silos and should be able to analyse business needs!

And finally

My concern is that organisations increeasingly see technology in its new guise as KM and are jumpiing on the bandwagon to put social tools behind the firewall expecting staff to find the expertise / historical knowledge automatically. In previous pieces I’ve argued that assisted search is still important.

I can also see a shift towards HR / Talent Management as the logical resting place for the discipline where the driver is one of mitigating the risk of knowledge loss when people leave.

But I still see in the short to medium term at least a need for what good KIM’ers do.

AI driven expertise & profiling: hype, hope or déjà vu?

May was a busy month. Apart from helping establish then launch a real estate and mortgage business (Bees Homes) I was in Lisboa for Social Now and London for KM Legal UK.

I attended both in the expectation of learning more about the onrush of Artificial Intelligence and its implications for the Knowledge Management profession.

Specifically, I wanted to see how the encouragingly styled Talent and Knowledge Matching / Profiling systems might tackle the challenges of knowledge loss when people depart, of onboarding when people arrive and identifying / ranking expertise that might otherwise be opaque when pulling together teams.

It’s not a new topic: back in the late 90’s I was Business & Strategy Advisor to Sopheon PLC when we acquired Organik (a technology for identifying expertise) and built systems for US Insurers looking to establish the best teams for clients based upon expertise. We never cracked it even though we knew what the issues were (usually motivation)!

Seeking answers at SocialNow Lisboa while Keynote speaker Ellen Trude watches.

Armed with a list of ‘use cases’ I’d worked on with Martin White I set off in search of answers to these questions from both vendors and KM practitioners?

  • Onboarding: A new employee with many years of highly relevant experience joins the firm. How long will it be before their experience is ranked at the same level as their predecessors?
  • Legal: Is the profiling process compatible with the provisions of the General Data Protection Regulation? The thoughts of the Information Commissioner on this are worth a look. Profiling & Automated Decision Making
  • Functionality: Do they offer the ability to present a list of people ranked by expertise?
  • Language: In multinational companies where it is especially difficult to know all the experts, how does the vendor coppe with the fact that documents, meetings and social media traffic will be in local languages?
  • Chinese Walls: How does the application cope with expertise gained on projects that are secure, a common issue in law, finance and R&D where walls need to be erected to prevent commercial information being divulged>
  • Testing: What User Testing is undertaken with a client before signing a contract to verify that the profiling system works?

So, what did I discover? Thierry de Bailllon in his closing Keynote put it very succinctly but with a caveat:

Embrace or die? 88% of technologies already include AI.

Self reinforcing bias?

it’s not Enterprise Social Networks (ESN)!

This Twitter exchange between Ana Neves and Luis Suarez prompted by a question I posed of the Workplace (Facebook at Work) team following their presentation is revealing:

May 12 there’s been a few questions about expertise location 2017 I don’t remember that being the case in previous years #SocialNow

May 12 Well, I think people are starting to understand how critical it is to know who is who within the org beyond just content, right?

Replying to totally! It surprises me it took so long. It’s amazing the role #ESN can have in unveiling that expertise #SocialNow

On the surface the case for ESN is compelling. Yet the majority of vendors at SocialNow focus on information exchange and conversation rather than the capturing and cataloguing of it. One,@mangoappsinc, had a neat tool (they won the “coolest app” prize) with the ability to upgrade comments from threaded discussions and posts to create ranked knowledge resources from the mass of information and conversation.

So, ESN can show who has answered what question, conduct searches across conversations and in many cases act as a project management tool, the new Facebook at Work (Workplace) now allows the creation of documents for example.

Provided the application is linked to HR systems it is possible to retrieve profiles and see what expertise an individual might have. As one vendor (@OrangeTrail showcasing Facebook at Work)) who uses bots to generate responses put it:

‘Questions’ is the key to find experts as people don’t keep profiles updated.

I concur and they are great facilitation platforms though with advanced features that will suffice for many. Yet I left Lisboa though feeling organisations will need to rely on assisted search for some time if they want to take a deep dive into expertise

know what you don’t know

Peer Assist “Problems” for discussion

So onto London and KM Legal UK. An interesting Day One ended with a psuedo Peer Assist in which AI was raised a lot.

One observation (facilitation tip): the session failed to commit the ‘owner’ of the problem to action so as a result the feedback loop to plenary became a series of “we said this.”

Again, as in previous years I felt the focus was on operational tools and techniques which means that KIM Professionals in Legal are more at risk from the onrush of technology.

It reminded me of the issue Librarians faced with the arrival of end user search in the mid 90’s which finished their monopoly of being the people who found stuff in organisations.

Day Two took a deeper dive into technology and its potential impact.

AI in Legal today

This slide sets out where AI is making a difference in Legal.

I tweeted having heard Cliff Fluet’s excellent presentation:

Paralegals beware. AI is coming. Adapt or die?

And I questioned:

How wide is scope of AI? More than Doc Analysis / Creation. Opportunity to broaden knowledge base

As yet no one had focused on expertise and profiling so when one presenter cited the case where a newly arrived CEO asked the Head of HR / Talent Management to let him have profiles / competencies of the staff using their system it got my attention.

I asked whether the results the HR head gave the CEO inferred a level of expertise. It didn’t which got thinking that if the data set is incomplete and the issue of self reinforcing bias is not addressed then over reliance on one source for identifying ‘experts’ is dangerous. Imagine your career prospects if for whatever reason your name wasn’t on the ‘expert’ list given to the CEO?

and finally

So where do I see the state of expertise and profiling systems? Patchy!

Yes there are certainly companies who ‘get it’ but can they do it?

I am indebted here to Martin White who in an excellent report “People and expertise seeking – an overview” summarises the predicament thus:

The most important lesson learned is the need for an expertise location strategy that is linked into HR processes, knowledge management, training, job appraisals and social media development. Finding people with expertise is not a ‘search problem’.  Good search tools can certainly help but without attention being paid to profile quality (even if other types of content are being searched) and a commitment by employees to share their knowledge expertise discovery will not be as successful as anticipated or required.

My takeaways:

  • KIM professionals need a clear strategy (working in partnership with other stakeholders such as HR and IT) and be clear on the questions being solved by any system;
  • They need to be clear what they are getting, what’s missing and how it mitigates the potential for self reinforcing bias when they enter discussions with vendors around automating expertise seeking and profiling;
  • They need to recognise the importance of their role in facilitating the adoption of such systems and accept this is just a part of a portfolio of approaches of identifying, capturing and retaining expertise;
  • They need to be clear what critical knowledge actually is in their organisation and who is likely to have it in order to assess the veracity of the results of any pilot;
  • It doesn’t matter what solution you adopt, if your environment is not conducive to the sharing of expertise and people don’t see the value in it then save the money; and
  • In any event you cannot capture everything people know; we learn and share through stories (failures rather than successes) and those often remain hidden.