Artificial Intelligence (AI) is “intelligence” that is not the result of human cogitation.
I followed the question on Quora What is the difference between artificial intelligence and human intelligence? and here are some answers from clever contributors
"Artificial means man-made. The only way we can be considered artificially intelligent is if we considered biological reproduction resulting in intelligent humans as a man-made process."
"We know that we are not artificial intelligence because we know that we are not artificial."
"In my opinion it is misleading to talk about "artificial intelligence". The alternative term, "machine intelligence", is far better."
Machine Learning (ML) is the subset of the Artificial Intelligence (AI) focused on algorithmic approaches, while traditional methods mostly use a parametric approach. Yet ML and AI are used almost interchangeably
Botchats
Botchats (simply called Bots) are illustrated like this in slackAPI manual
Using Artificial Intelligence, I have a bot mimicking me in a supermarket receiving instructions from my wife on what to buy. This is best done with a pencil and any piece of paper. But in this case, my Bot named Officebot talks to my wife Bot called Celeste.
Bot users have many of the same qualities as their human counterparts: they have profile photos, names, and bios, they exist in the team directory, they can be direct messaged or mentioned, they can post messages and upload files, and they can be invited to and kicked out of channels and private groups.
The biggest difference between bot users and regular users is that instead of interacting with a team via one of Slack's mobile or desktop apps, bot users are controlled programmatically via a bot user token
On a web site a Bot greeted me:
The bot: May I help you?
Me: Are you human?
The Bot: Yes I am
Me: Prove it me you are human
The Bot: I can answer your questions
This was a clever little bot.
From AI (Artificial Intelligence) to AN (Artificial Narrowness)
An article on Tech Target: If Chatbots are trend #1, this is trend #2
The second macro push came from Facebook's Mark Zuckerberg. In April Zuckerberg announced that Messenger was going to be extended from its origin of friend-to-friend communication to consumer-to-business applications. Even beyond allowing you to chat with businesses, he was specifically referring to the ability to embed that artificial intelligence into Messenger.
The author sees the future of bots in human resources
The values of self-service transactions in HR are
Candidate self-service
Manager self-service
Employee self-service
Not only your resume lands in an enormous database untouched by human hands, the follow-up is using bots. As a defense in the future, it would be better to apply to a job using ten or more bots, with ten or more different descriptions of yourself.
We just had a peek to an Orwellian future. The my-bot-speaks-with-your-bot is not going to work as it goes against spirituality
Happiness
Artificial intelligence usefulness is not apparent to every one
Lets assume an author who is adapting complex ideas for public consumption must be a.) capable of understanding the ideas thoroughly in their original form; and b.) familiar with the limits of understanding of the general public and the way these materials must be presented to them.
This author is a "man of God" . It comes from a commentary to Psalm 90 by a great scholar. Moses was the only individual capable of transmitting the Torah from its heavenly sources to earth
Over 50% from all life experiences are emotions and these emotions drive primarily our behavior. In business as in our personal life, if we deal with customer experiences without considering emotions, we are not doing our job.
2008 Global Customer Experience Management Survey from “The DNA of Customer Experience: How Emotions Drive Value” by Colin Shaw.
We do not make money as a business organization by cutting customer service jobs and replacing people with bots. We make money through people
Bots are useful,
ML is great but
Happy employees enable happy customers.
“No business has ever failed with happy customers”, said Warren Buffett, May 2016.
Machine learning is here to give the management a view of profits, along side the human assets sentiments who are the true generators of wealth in well managed companies.
Machine Learning should justify how employees, working closely with prospects and customers, can generate 100x, even 1,000x more business than the meager , short term savings when replacing people with bots.
One can not have ultimately a company made out of token activated bots.
Imaginative uses of ML
The article why Good Companies Go Bad from Harvard Business Review 1999, describes the term Active Inertia. This is an organization’s tendency to follow established patterns of behavior—even in response to dramatic environmental shifts. Many large companies fall victims. Machine Learning may have access to documents where it can extract proof of the Active Inertia. Than the management makes changes and see if the symptoms of Active Inertia are less than before.
The happiness literature has identified one of the most deeply satisfying human psychological states to be one called “flow.” It occurs when you are so immersed in an activity that you lose track of the passage of time. Can we identify roughly what is the the percentage of total employees who experienced it?
Finally, we want in our country to give people the ability to work productively in steady jobs, without the stressful fear of being riffed. Most humans are not entrepreneurs and are risk averse.
Look at Intel, Cisco, and the like laying off people in massive numbers. They could have had avoided it is they have had identified the Active Inertia in their companies and the lack of flow in their employees.
Machine Learning can transform our world, as long as we know how to use it.
I saw a new start up who wants to teach very wealthy people how to invest on Silicon Valley firms, without any previous high tech experience. I shook my head: AI alone, can not answer their questions, unless they want to loose their shirts off.
First published here
