AI and machine learning are all the rage, but the key is how they’re
used. You can’t just throw AI at a problem. For some of the most difficult and
nuanced challenges, AI needs to be taught – by humans. We’re using AI and
machine learning in our platform to discover value in massive datasets, and we
certainly need human input. Human input from our team and our clients.
The three main reasons AI needs humans is because AI is immature,
people and machines working together provide the greatest value, and finally,
true creativity is led by humans.
1. AI is a like teenager.
Today, AI knows what it’s been taught but left to its own devices,
it doesn’t always make the best decisions. Think of a 14-year-old going out
into the world and left to do as they please… you get the picture. An example
of AI that hasn’t met business and user needs is seen today with Facebook and
Google. They are both feeling the pain from AI and machine learning failing to
fit the bill.
Facebook’s AI failed to detect fake news, hate speech,
discriminatory ads and terrorist propaganda. Zuckerberg referred to AI
technology more than 30 times during his testimony to congress and said in the
next ten years it will be a sophisticated tool to fight against these issues on
its platform. (Washington Post, 4/11/18).
Last year, Facebook also shut down a project in which two AI platforms
began having a conversation with each other using English words but not in a
way people could understand. It had apparently developed its own shorthand.
Google has a similar issue as Facebook with offensive content on
YouTube including extremist content, compromising images of children, and hate
speech. Not only was the content shared on the platform, but major brands were
also programmatically (and unknowingly) buying advertisements alongside this
content. YouTube and the content publisher both benefited financially from this
content. More than 250 brands responded by pulling their ads from the
One of Google’s most recent AI developments is Duplex, an AI
assistant that sounds like a human complete with ‘umms’ and speech patterns
that can make phone calls and speak with a human without the human knowing it’s
a robot. It’s an AI feat for sure. The question is, when asked, will this AI “teenager”
just book the table for 2, or will a confused real teenager on the other end of
the phone manage to confuse the AI and take it out of previously learned
2. People + machines.
The most value comes from people and machines. It’s not realistic or productive to debate people
versus machines. Facebook and Google are now hiring tens of thousands of team
members to help clean up their content and advertising platforms.
In response to Facebook’s data privacy scandal and the hiring
they’re doing, Mark Zuckerberg said, “It's not all A.I., right? There's
certainly a lot that A.I. can do. We can train classifiers to identify content,
but most of what we do is identify things that people should look at. So we're
going to double the amount of people working on security this year. ... So it's
really the technical systems we have working with the people in our operations
functions that make the biggest deal." (CNBC, 3/23/18)
In response to YouTube promoting offensive content, YouTube’s CEO Susan
Wojcicki said, “Human reviewers remain essential to both removing content and
training machine learning systems because human judgment is critical to making
contextualized decisions on content.” (The Guardian, 12/4/17)
We’re building a software company and a consulting firm wrapped
into one for these very reasons. Usually, these activities are separated, and
that’s actually how we started. However, we quickly realized we were missing
some incredibly valuable insights in our AI and ML platform that the consulting
business brings. Our consulting projects are benefiting from insights derived
from our software AI and ML. Our software development is benefiting from smart
people matching its capabilities to client problems and providing a feedback
loop for development.
It’s important to apply HI (human intelligence) to software
development and technology implementation from the earliest stages. Bill Gates
said, “The first rule of any technology used in a business is that automation
applied to an efficient operation will magnify the efficiency. The second is
that automation applied to an inefficient operation will magnify the
3. Creativity is human.
At this point in development, AI is “narrow AI” – it’s able to
do specific tasks really well and often times better than humans. Those tasks
include classifying images, playing chess or Go, generating safety alerts in
vehicles or even calling a restaurant to make a dinner reservation.
To be creative, humans need to lead the way. Computers can create,
but to be creative in a way that provides meaning to humans, wisdom must be
applied. Jack Ma said it best, "Human being[s] have the wisdom. Machine[s
do] not have the wisdom." (CNN, 9/20/17)
Human-level AI that can understand and reason as a human would is
still elusive. The way humans perceive, sort through unrelated thoughts and
memories to reason and make nuanced decisions is extremely difficult for a
computer to replicate.
creating a data decision platform. Decision making needs to be based on
business growth objectives and how teams within the organization use and work
with data to do their jobs and inform decision-making. Our consulting team is
the “HI” that understands the business need and understands the people in an
organization that makes success happen. Over time, as our platform matures and
becomes more intelligent, our HI will minimize in certain contexts.