My name is Guntram Werther,
I'm Professor of Integrated Business Applications Group
at the Fox School of Business, Temple University.
Today's talk is the "Machine-Human Interface.
How to Better Judge Emerging Events".
We have wonderful new technology.
It allows us to do all kinds of new things
and we're still working with the same human skill sets.
I think this has happened several times in
human history and what we're talking about today eventually
is going to require that we build up those human
skill sets to interact more effectively with that new technology.
And I'll try to show that to you with some data I have and some other comments.
So, the problem is improving machines with the same old human judgment.
I have some data from the US and Canada, primarily.
The first is average integrative thinking ability of
experienced intelligence analysts we're looking at
15 years or better is about a 1.5 on a five-scale.
This is from the Director of National Intelligence, United States.
For industry, also again,
15 years of ability for the average analyst.
These are very experienced analysts in the world's largest companies.
They self-rate the ability to take machine and arithmetic outputs to
create effective real world judgments at about a two to three out of five-scale.
And then if we ask them what happens in a rare event or crisis event, again,
the average ability to take that machine/arithmetic output and create
effective real world judgments falls to about a one or two on a five-scale.
Now, these are self-judgments,
they're done informally so as not to embarrass anybody.
But I'm pretty sure if you do this in Europe and other parts of the world,
you're going to come up with roughly parallel information.
Certainly, you're welcome to do that on your own but
that's my finding over the last several years.
My main theme today is that the biggest real world assessment challenge in emerging