Thierry Hubert and I recently gave a webinar on the Human Side of Content Monitoring through the Marketing 2.0 network run by the Human 1.0 group. The session was recorded and we will soon make it available. Human 1.0 is in business to help you turn your customer-facing processes into social processes. I am part of the their network of consultants. They also manage the FastForward and the AppGap blogs that I write for. In this post I want to share some of my opening comments that provide context for the Darwin Awareness Engine™ and address the issue of when to use computers and when to use people and how to best have them work together.
One of our favorite books is Don Norman’s Things That Make Us Smart: Defending Human Attributes In The Age Of The Machine. In this book Norman argues that it is time for us to adopt a more human-centered perspective and to insist that informational technologies enhance and complement human cognitive capacities rather than undermine them. I have worked in many situations where the role of the machine and the role of the person was in dispute. For example, in developing support systems for call centers, I always tried to provide the reps with the right content in context and access to the right people so they could intelligently deal with customer questions. The same approach was also applied to insurance underwriters.
Well others wanted to create automated scripts for the call center people and automate the underwriting decisions. Guess which approach the people favored. Fortunately in the situations I was involved with the people won.
This is also our guiding principle at Darwin. We want to better enable people to make decisions by using Chaos Theory principles to let the content self-organize and then creating useful content visualizations to facilitate the human mind’s ability to sort through content as you will soon see. It is the opposite of semantic technology that tries to get the computer to understand language and do some of the cognitive work. There can be a place for both.
So you can dumb down a task or smarten it up. Now there are perhaps some things that computers do better than people. IBM’s Watson has demonstrated that you can build a machine to handle some level of cognition. However, this takes considerable effort. Watson was built and trained by a team of experts over a number of years. It uses math algorithms coupled with semantic analysis to allow it to understand a natural language question and determine the probability that its answer is correct.
However, Watson is good for a very specific task and it is not perfect. The years of training may make it better than most, if not all, humans in playing Jeopardy. However, it will fail against humans in most of the other tasks we face every day. In fact, recent research noted that all the computers in the world have now reached the processing capacity of one person.
So the issue is not whether computers will outpace people but how the two can work together. Computers are very good at doing boring tedious, repetitive tasks than would drive people crazy at a rate and scale far beyond what people can do even with a fresh start on their best days. This frees people up to do the more complex and interesting tasks. That is what we are striving for with the Awareness Engine.
The Harvard historian Niall Ferguson wrote, “It is the unforeseen that causes the greatest disturbance, not the expected.” One of the skills that people have over computers is knowing where to look next and to quickly see anomalies. If you dumb down a task you will likely take away the person’s ability to see the unexpected. You will reduce discovery and stifle innovation. In contrast our scan cloud visualization displays the top 100 themes within your content of interest so you can quickly sort through them (see below for an example looking at social media issues over a recent 24 hour period). Here is an orientation video. The more you know about a topic the more value you can derive from this Scan cloud.
For example, during a presentation we did of the Darwin Awareness Engine to a large energy holding company, the information curator, responsible for providing the CEO with reports on all public, political, and news events related to the company’s business and its owner’s public image, spotted the term “London” in the ScanCloud. Most other terms and their highlighted relationships where within the expected context, but “London” was an anomaly (only someone with an intimate understanding of the company’s activities would have made this assessment). She asked to be excused for 5 minutes and returned to the meeting.
She shared with us that despite the tools currently available to her to comb the Web and the press, she had not noticed the event she just discovered using the Awareness Engine. In fact, the event related to the violation of a UK court gag order that could have caused material damage to the company. She identified the blogger and reported it to the Legal department. Subsequently, she added the event to the CEO’s daily report.
External algorithms and machine driven intelligence rely on rules and predetermined taxonomies that can hide the unexpected. People-centric tools can enhance our natural, and perhaps evolutionary, cognitive abilities to notice the unexpected. The graphic below that Thierry created illustrates some of these contrasts between machine and human intelligence. Both have their place.
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