Artificial Intelligence is a tough nut to crack. The goal is simulate human behavior.
So let's say we train a neural network to learn behaviors, traits and characteristics of human behavior.
For example, we teach the machine the process to dispense coffee at a coffee store. We train the model, test and score and evaluate the results.
And we find some startling results. Although the process of taking a customers order shouldn't vary, we find the results are all over the map.
Some customers are not satisfied with their drinks, some are oblivious and some are very satisfied. But why is that? If the process never varies, in theory, we should see similar consistent results every time.
So if we dive a little deeper, we find some interesting things. First, there are many variables. Some are known, others not known.
For example, client A got decaf coffee when he ordered caffeinated coffee. Let's review the tape. Well, bartista 1 took the order, processed the order and delivered the order. According to the tapes, they performed their job as expected. Let's ask bartista A a few questions.
Did you perform your job as expected? Yes, the order was taken in timely manor, processed the order as expected, and delivered within timely manor. Yes, but you gave decaf when they ordered caffeinated. Oh really? I'm sorry, my bad.
This could be chalked up to many factors, some obvious. Over worked. Not paying attention. Read the order incorrectly. Or it could be something else.
Let's look for the non obvious. Perhaps the client looked like his/her ex-wife/husband, get back at her/him. Perhaps the bartista is late on their rent, drank too much last night, not focused on their job.
Perhaps they are unknowingly upset with themselves for their life situation, they should have studied more in school, now in a dead end job. We'll make sure everybody is as miserable as me. How about a nice hole in the bottom of the cup, you'll enjoy the coffee dripping when you get to your car. How about we forget to include your donuts with your order.
Or the opposite, how about we give this person exceptional service? Because they look like me or they have similar tastes or interests.
Let's apply this rule to everything, everywhere: let's discriminate our behavior and services to our clients, based on internal bias, prejudices, beliefs and opinions.
Let's vary the outcome based on slight deviations from the actual process.
First off, many of these incidents don't get reported. Second, nobody investigates why. Third, the person may not even be aware of their errors. So nothing gets corrected.
This scenario could be described as a black box. And we typically don't know what happens in a black box. Magic.
Yet if the process is identical and the results vary greatly, we must account for the variations of end results. We need to explore the black box a little deeper.
And when we look closer, we see people performing the job descriptions as expected, yet with a bit of undocumented wiggle room. Which result in varying results and outcomes.
Loose lips sink ships. And varying from the process skews results. And the results are based on undocumented internal bias.
Once we identify the patterns, the trick is to correct them. How?
Implementing guidelines, such that, there is no wiggle room for error. Remove the barriers for deviation. By following the prescribed pattern of actions, you can consistently provide results within expected statistical ranges.
Bartista: Listen, we know you are paying the same amount for your coffee, but I don't care for you, so I'm going to vary your order just slightly so that you get sub standard service or product.
Personally, I find this scenario to be widespread and prevalent in our society. You can apply this formula to just about everything everywhere. Yet nobody knows it exists or aware of it. A silent, invisible signal affecting the outcome of everything.
I find it to be the source of chaos, confusion, corruption, and a vehicle to spread negativity into the world.
When duplicating human behavior, we need to dive into the behaviors and processes to investigate. We have to account for the variations in results. And look to the reasons behind them. I believe those deviations stem from bias and discriminating factors within the system, undocumented and unaccounted for, yet present.
We need to remove these variations from the equation. Through process. Documenting, Workflows, Business Rules, Implement through technology and algorithms. To prevent unknowns from the equation. For consistent patterns and results.
Then monitor results and modify to self correct on the fly.
By streamlining processes, we can ensure quality service across the board. This should reduce costs from having to correct problems downstream and customer retention.
If we matched human behavior 100%, we'd need a function to simulate stupidity, biases, prejudices, hatred, vengeance, revenge, evil, etc.
We need to automate everything. Remove the human factor which is tainted, biased, prejudiced and inconsistent. I think this is the key to fixing a lot of systemic problems in every aspect of everything on the planet.
Automate. Remove bias. Streamline. Measure. Repeat.
And the vehicle to automate this is called Artificial Intelligence.
I signed up for the Hortonworks Certified Associate exam last Thursday. Figured if I sign up, I'd have to take the test. And if I tak...
Saw a post today on Twitter, " Microsoft releases CNTK, its open source deep learning toolkit, on GitHub " This is big news. Be...
It seems like open source applications are the mainstream today. So many new products delivered through Aache foundation. Some do this. S...