- We've seen that artificial intelligence
started with the general problem solver.
This system used symbols
to explicitly program a computer's response.
Then just a few years after the first AI conference in 1956,
we saw the beginnings of machine learning.
Here, instead of programming,
the system learned by looking at patterns in data.
Now AI systems are integrating themselves in the workplace.
They can tackle complex problems
and can even come up with creative solutions,
and this is why it's important to understand
how these systems operate.
Most people who interact with AI systems
will not be data scientists,
many of them will be business people and entrepreneurs.
In fact, there's a pretty good chance in the next few years,
you will be working on an AI project.
Just like how managers work with software developers today,
these same managers will start to work with AI systems
and data scientists tomorrow.
Don't believe me?
Imagine someone on your team sent a report
on AI that sounds like this,
"Managers need to be able to set the right goals,
evaluate results, and give feedback for AI."
Just like any technology,
AI needs to be managed effectively to be successful.
Here are a few things to remember about AI.
First, AI systems are only as good
as the data they're given.
This data needs to be accurate
and representative of the real world.
If it's not, then the system will learn
from these inaccuracies and produce inaccurate results.
Second, AI systems learn by trying different things
and seeing which ones work best.
This means that there will be some trial and error.
As a manager, you need to be prepared for this
and have patience while the system is learning.
Finally, AI systems can do things that humans can't.
They can process large amounts of data quickly
and find patterns that we would never be able to see.
However, they still need supervision and direction.
With these three things in mind,
business people can start thinking
about how they will work with AI systems.
They can start thinking about the problems they want to solve
and how they want their systems to solve them.
Now, most of what I just said was written by an AI system.
It was written using GPT,
or Generative Pre-trained Transformer 3.
This system is commonly used
for natural language generation.
The AI system scanned through millions of articles
on artificial intelligence
and wrote out what I said after a short description.
Then it used a deep learning artificial neural network
to find patterns in articles about business people in AI.
It then just reassembled these common patterns
into a few paragraphs of text.
So now you can think about the ways
that AI systems can help you or your organization.
What type of data are you collecting?
What would you want to know about your customer
that might help enhance your business?
Or if you want to work in the field of AI,
then think about what problems you hope to solve.
In the next few years,
these systems will become eerily more human.
The organizations that create the best AI systems
will be the ones that enhance
and not replace human creativity.