Episode Transcript
[00:00:00] Speaker A: Foreign.
Welcome to Ever Changing Technology.
I'm Jim Bradfield. From point A to point B, navigating the evolution of innovation, Technology never stands still. And right now, artificial intelligence is redefining how we live, work and decide.
Joining me is Dr. Zedek Hakim, Associate Provost and Associate Dean for Online Technology at Houston Christian University, professor of information sciences and cybersecurity, and former global executive across energy and telecommunications. He provides strategic leadership, online education and technology initiatives, overseeing academic quality accreditation, student success and program development.
Man, that's a lot.
In addition to his academic leadership, Dr. Hakim brings more than 15 years of executive experience as chairman and CEO in the energy, telecommunications, in international consulting sectors.
So he has led multinational organizations, guided IPOs in major contract negotiations and government boards, and overseen strategic growth initiatives across the U.S. europe, Asia and the Caribbean.
Man, I'll tell you, that's an awful lot there. Dr. Hakeem, welcome.
[00:01:43] Speaker B: Thank you. Thank you, Jim. I appreciate the opportunity.
[00:01:46] Speaker A: Yeah. So we, before we get into the technology itself, let's define your mission. Because leadership shapes how innovation gets deployed, let's start simply. What is artificial intelligence?
[00:02:01] Speaker B: Well, to answer the first question, what is my mission? I actually focus my mission. Three pillars.
The one pillar, it will be innovation.
The second pillar will be protection.
And the third pillar will be strategic leadership.
That is to say that bridging technology and strategic leadership to actually drive and focus the landscape digital transformation.
Those three pillars are very important in any technology, in education and anything underneath the sun. If you can apply those three pillars in any technology, you will be off to a great start.
Now as we discuss and your second question is, what is artificial intelligence?
Artificial intelligence, it's a new domain that is more or less, it's a machine learning.
Artificial intelligence is different from human intelligence.
Human intelligence and artificial intelligence are very important in today's environment.
Artificial intelligence is the ability of a machine to learn from, pattern and produce outcome.
And that is predictive outcome.
It is probabilistic, it is not deterministic.
To say is that artificial intelligence is the combination of the domain of computer science and large data set. The main idea is to start working together the data set. And as you can see in this slide that you put there, 90% of the data of this world has been driven in the last two years. That means we have a lot of data, enormous quantity of data that we need to go through it. And that's what we call dark data.
This dark data, for us to understand it is very difficult as a human. That's why we use machine to help us Gather the information and at least help us understand the domain of that information, comparing it with patterns to produce some outcome.
In this world, actually you will have 7.7 billion people on the face of the earth producing data on daily basis.
That data it is not clean data. That means it is not structured. In other words, structured data is what you will go to your computer and see a spreadsheet with title.
And that will be the different characteristic artificial intelligence. It is not only for structured data, it's for unstructured data. And that's how we will help us make a better decision as a human and find the proper answer from the machine probabilistically to do more or less the solution for human problem on daily basis.
So that's the main idea is machine we have to understand is a machine does not think, does not analyze, does not sensitize.
It's only predict the outcome. That what is artificial intelligence? And that is how it's used today.
And we can go deeper in it, if you wish. But there is a different tool that artificial intelligence is done today.
There is the machine learning in different types to understand machine learning processes.
The first type of machine learning is supervised machine learning. The second one is unsupervised.
And the third one, actually it is a combination of the first and the second supervised system.
That is to say that for a machine to help us predict the outcome in the supervised system, we have to give label to the algorithm. That means, let's suppose an individual that work in the supermarket and they are going to gather oranges.
They put label on the oranges to identify. Then the machine will scan that label and say this is an orange, the other one is an apple.
But in the unsupervised system is when you don't give the machine a training model, the machine you'll ask the question, give the information and the machine will go and work by itself to give you the outcome.
Now the reinforcement learning is very important because it will be error, try again each time that the machine will go until it receives a good outcome. And that's how machine work to help individual to make a better decision.
That is more or less a global information about artificial intelligence, right?
[00:07:16] Speaker A: And so you know, you were talking too about artificial intelligence, but requiring human intelligence, right? So it's a. It's a completely separate thing. We need human intelligence that, right?
[00:07:28] Speaker B: Well, definitely. Now human intelligence is very important.
When you drove today to your office, you use three type of intelligence today.
The first intelligence that you use is machine intelligence, which is artificial intelligence by itself.
Then you use human intelligence, which you are. When you went, picked up your key and went into your car and turned your car on.
Then when you turn your car on, you went on the highway and set out the speed limit, automatic. That is a machine.
But now when you combine machine with individual, that what we call augmented intelligence.
Augmented intelligence. It is very important. The machine itself, what we have artificial intelligence, will ingest a lot of data, enormous data set to analyze it. The dark data that we discussed before, about 90% generated in last year.
And what it will do with it will make a repetitive process over and over and over again with accuracy.
Now let's go to the individual as human. What we do is we are good in taking a piece of data and, and make generalized information on that.
And we are good in being creative. The machine does not do that. We are good in thinking and analyzing. The machine does not do that.
And we have human intelligence. That is, well, we are emotionally intelligent. That's very important. That's the huge difference between machine learning and human.
I can see something and it make me cry.
My tear will come up. I have emotional intelligence.
I can decipher. When you smile at me, I say, he's a good man. That's emotional intelligence. I'm reacting to your, to your presence.
Machine does not do that. Machine will predict the outcome. Like, I'm going to a doctor. Right?
[00:09:36] Speaker A: Right.
[00:09:37] Speaker B: And the doctor will come to me and they said, what you're here for? Well, I have pain in my heart in here.
He will take all the information, give it to the machine about my history and everything.
Then the machine will come back and say, depend on the historical background of this patient.
I can predict that 95% of this medicine can help and predict it probabilistic. It is not deterministic.
But there is another way that 80% of the medication will help it.
Then the doctor will come with the patient and decide which probabilistic answer will be good for the patient. That's very important to understand the practical element of the machine and the human and contribute them both together. That's what we call augmented intelligence and artificial intelligence.
So the human is still very important.
And spoiler alert, the machine does not think, does not analyze, does not have emotion, does not cry. That is our job. That is our duty. That's how we were formed before.
[00:10:53] Speaker A: Right? Yeah. So we've got a couple minutes left in this segment, but what responsibility with the training of the next generation of AI leaders is required? I mean, there's obviously something that we've got to make sure that happens to keep everybody on the straight and narrow with us.
[00:11:14] Speaker B: Let's understand how we work with artificial intelligence to answer that question.
We give the information label, we code the algorithm, depend on the individual coding the program.
That how we guarantee that we have unbiased decision in the code depend on our input into the equipment, into the data that what will perform. So what we need to take care of is that we hire good individual with good principle with actually liable to their constituency to do the right thing when they code the algorithm. If they code it wrong, suppose they have an individual working in finance and he will code the database of that machine to spit $1 each time for him when he is printing the check for other people. That is not good, that's fraudulent and that depend on the human actually.
So what we have to make sure is we employ ethical people and put in place ethical governance and policy. Clear, crystal clear to protect the organization and at the same time educate the education and train them how to use it in the proper way.
Right.
[00:12:38] Speaker A: All right, so so far now we've defined the mission and the foundation. So you know, when we come back we're going to unpack the systems and address the fear versus reality conversation around AI. That's an awful lot of things going on there. So we appreciate you and we'll talk to you in a few.
[00:12:56] Speaker B: Thank you sir.
[00:13:00] Speaker A: And we're back. I'm Jim Bradfield and this is ever changing technology here on Now Media Television.
This is ever changing technology on Now Media Television. Watch anytime on the Now Media Television app available on Roku, iOS and Android or stream at www.nowmedia.tv.
welcome back Dr. Hakim. Let's go deeper into this, how everything actually works. We live in a world of nearly 9 billion mobile devices generating quintillions of bytes of data every day. That scale changes everything. That is amazing.
With those 9 billion connected mobile devices, more devices than people, how does this level of connectivity accelerate AI development and change human behavior?
[00:13:59] Speaker B: Actually we are living right now in the era of broad AI.
We have three different era for the era how we started and when we started with the definition of artificial intelligence like around 1953 to and when we lived in that era, we were living in the era of narrow AI. That mean our system was limited and weak and responsive and teaching. Now we are in the era of broad AI. That means our equipment, that is the machine learning system, can teach physics, can teach architecture, can teach somebody to code, can speak with somebody and transform information into data or data into information. At the Same time.
So there is an interaction now with the machine. At the beginning it was limited, like Siri, what is the weather today? So Siri will answer and say the weather X, Y and Z. That is the narrow AI era that we were living in. Now we are living in the broad AI that we can label the product and we can ask the machine to give us some information and predict the outcome of that. And the other one that we discussed few minutes ago is the second one is the unsupervised. That will give the data to the machine. No matter how big is the data set, we ingest it into the machine and then we ask a question so the machine will go on its own and give us the answer. And today, as you said, we have vast amount of data in the market coming from everyone.
And this data that we show in the slide, that is actually about six years ago, it is not new. We don't have new data as you seen in there.
But as you will know, that is 7.7 billion people on the face of the earth.
That mean it's growing on daily basis. And for that we need element in our hand to work with and structured data.
In the year like 700 BCE when the Chinese start building the wall, the emperor needed something to help them understand how much money they need to finance the wall and get the write the resources to build the China world. So what they did, they created. Somebody came with the idea to create the abacus table and that tablet. It was a beat table that they can add and subtract using the beads. Moving forward a little bit, we start working with the typewriter. But then individual they come and said, well, it is too slow. How I can type faster and put it in a memory. They come with the word processing machine and then we start growing forward step by step until we start using the mainframe. And now that we have moved into the era of broad AI, that means we can use artificial intelligence and we can go through the vast data that we have to organize it. Now let me share with you like a researcher what a human does and what a machine does.
As a researcher, I will go and collect data from the field. I gather the data, I clean the data, analyze the data. And once I analyze the data, the data start making sense to me in what I'm looking at. If you have seen some accountant looking at their computer sometime you think that this guy is crazy. He's looking at that and he's talking to himself. No, he's not talking to himself.
The data is talking to him. It's giving him insight. Now he's into the data, penetrating in the data to make sense of it. Once he get the information and the data, then he will make a decision based on the data collected. Now let's go to the machine. The machine now it is not thinking.
The machine will go and look for data and what is being ingested and start discriminating between probabilistic information.
That means it will give you 80% accuracy in this or 90% until it comes to the point that will give you some information that you can get in your hand.
The artificial intelligence, what it will do is gather that data, but does not think about the data.
The human does that.
Know that enormous data set that we have now we can ask the machine to help us understand it so we can make a decision based on the recommendation done by artificial intelligence. That is what it is going on now. And now when we move from the era that we are in broad AI, we go to general AI.
Now, as we discussed before, human can have emotional intelligence.
Machine at this point does not have emotional intelligence, nor it's creative.
But in the general AI, hopefully in the 2050, 2060 and further, then the machine will have the ability to have those characteristics that the human have. Hopefully will not be going dead there. But that is the place where we are going with what we call quantum computer. And there we're actually will be looking a general AI to get that enormous type of data, analyze it and help the human to make a better judgment so we can solve real world problem on daily basis.
That was the most important thing about that data.
[00:20:03] Speaker A: Amazing. Yeah. So we already kind of Talked about there's 2.5 quintillion bytes of data daily, which is just phenomenally unbelievable and that it becomes data intelligence. And you know, you're talking about what the humans have to do, but with the augmented intelligence we discussed earlier is, is it a more, is it a more accurate description of how AI should function with augmented or you know, with that, that intelligence from human being intervention?
[00:20:38] Speaker B: It is really, really. It will operate in different form on the collection of data. Because that is a huge amount of unstructured data. That's a dark data that's being generated. In the last two years. I said the slide.
So in this opportunity now in generating the 2.5 quintillion, that is 10 to the 18 power, that is a lot of data.
It is not something that you can put your head around it. That's why we need a machine to help us predict the outcome, help us navigate into that World of uncertainty to find the solution. And that's what we are coming slowly navigating through that one. And as you seen from about 10 years that we started with artificial intelligence and focusing in the last two years you have heard about artificial intelligence everywhere you go.
Now a lot of people, they are shying away from it because they don't understand it. They think that artificial intelligence take over the human job. That is not true. We need artificial intelligence. Like you need your car today to drive from your home to your office.
But your car is not going to drive, somebody else is going to drive you.
Now you think that the car is not good so we'll have a donkey to take a store, office. No, we need a car to go from one place to another. Like your segment from A to B. That's how a human need to understand technology and how use it. Like I'm an early adopter, probably you are too. I love technology. I like to jump on the wagon right away. Because if I don't jump on the wagon right away, guess what? That wagon is going to go in front of me and it's going to be very late to understand it. So people today need to understand it and not only understand, but apply it.
Artificial intelligence is here to stay. It doesn't matter what we say, but technology is going to be moving forward. We like it or not.
[00:22:43] Speaker A: So let's talk a little bit about that with cyber. How does cybersecurity evolve when the AI systems are trained on such a massive, constantly flowing data stream? How does that work?
[00:22:55] Speaker B: Well, it is really very important. Artificial intelligence is going to help us and protect our infrastructure. As you asked me at the beginning, what is my mission? I shared with you three different pillars. The first pillar is innovation. The second pillar is protection.
So innovation and protection, they come together in what we call cybersecurity protection.
How we do that in today's world, as we create a solution, there is a lot of people creating ill intention. On the other side, we are making some dollar in here and other people, they want the same dollar. So what we do is we have to embed artificial intelligence application inside the smart system to be a decision maker to protect and detect ill intention in that domain. And that is going to help us actually navigate and protect us and protect the environment that we are working in today. Actually, it is very important. There is a lot of critical infrastructure that is being vulnerable for a lot of attack. Why we don't have the capacity to understand the data. And that's where artificial intelligence can that you can Embed it directly into the smart system and it will operate as supervising detecting system to prevent from outside hacking. That is the most important thing that we are looking at today and how artificial intelligence is going to help you. But artificial intelligence cannot do it by itself. They need the human to decide on the outcome. This is where we are today. Maybe in the future.
We don't need artificial intelligence to work with it, it will work by itself. But human and artificial intelligence, they need to work together, contribute to find the solution to the problem.
[00:24:49] Speaker A: Excellent. Now just real quick, we have about a minute left. Where do most AI implementations fail?
[00:24:56] Speaker B: Well, it failed because most of the application use people that are not trained in it.
You need to train your employee, your stakeholder into the application of AI and at the same time you need to put policy in place. And in that policy you have to make sure that there is actually a repercussion, there is a correction, there is something that you have to manage on daily basis to protect everything.
So if you don't train your individual in the use application and deployment of the product that you are using, it's going to fail.
You have to understand it, apply it and use it to the benefit of the environment and the human.
[00:25:41] Speaker A: Perfect. So when we return, we're going to move from theory to application. How individuals and industries actually use AI to solve real world problems. Stay tuned.
And we're back. I'm Jim Bradfield and this is Ever Changing Technology here on Now Media Television.
We're back on Ever Changing Technology with Dr. Zadak Hakeem. Now let's move from systems to execution. Technology only matters when it improves outcomes. So let's talk practical impact now.
Dr. Hakim, how can individuals use AI today to improve decision making in everyday life without, you know, becoming dependent on it?
[00:26:34] Speaker B: First of all, as we said in the last segment, you have to train the individual NDUs of the AI and once you train it then it will be practical to use. But you need to know which application you are going to use. AI is a vast domain. AI is the name like a cafeteria. You have a lot of element in it. Now as an executive you need to find the proper application and tool to apply that AI in your work environment.
You are going to apply it in medicine so you'll have a different application there. You are going to apply it in cybersecurity. What we spoke before the segment. Then you have to find another application to protect the infrastructure.
You need to know which application you are going to do. There is a lot of good application in the market that you can use it on daily basis for administrative work like Copilot, that they just put it on the market. It's an excellent tool. Administrative tool not only will help you with the meeting, but it will draft the result of your meeting. It will make some question, it will give you analysis. That is artificial intelligence in the making. The other artificial intelligence that we are using actually in. In many domain in medicine now they are getting into the disclosure and analyzing the data. How to cure cancer, that is very beneficial. But they need to use the proper tool to utilize it. I heard about another experiment that they are doing in some other country that they are now injecting pot inside the human to find the cell and destroy the cancer cell inside the human.
We are using it to our benefit. We are using it to improve our life. What we could use in 10 years working on it to find the solution. Artificial intelligence will reduce that time to minutes or date. And when we move in the general AI, it is not going to be minutes, it will be millisecond.
Quantum computer, it's coming and we are using quantum computer right now, but we are heading into that domain. And quantum computer, it's going to be the solution to a lot of problems that human cannot even understand at this point.
[00:28:59] Speaker A: Yeah. All right, so question on industries like aviation, where a single airplane can generate terabytes of data daily, you know, where does AI create the greatest operational advantages?
[00:29:14] Speaker B: Well, because of the prediction that AI can give us a probabilistic prediction on the best usage of the product and the best uses of the flight, then that data can be reduced and depend on the weather condition when that airplane is flying, then you can navigate through it through the action of AI. That will save you time, an investment. And at the same time, the data will be cleaner than that among data that is feeding into the computer. So it depends how you are going to use it. In your case, in an airplane, it's very important because a human does not see further than where he's sitting in the pilot seat. So the artificial intelligence is navigating ahead of the game to prevent from an accident, to prevent from any collision, to prevent from any product that is coming there. So we are detecting and we are prognosticating what is going to happen to help us minimize any unfortunate accident.
[00:30:22] Speaker A: All right, well, that's awesome.
So in infrastructure and smart systems such as smart meters and connected utilities, now how does AI improve resilience and forecasting there?
[00:30:36] Speaker B: Well, because artificial intelligence will be embedded inside the smart system. And that smart system, now you have it there embedded and it will work as a supervising system to protect the information and at least make an awareness of what's happening inside the system. To protect actually from ill intention, to protect from bad operation or to at least alert you from something that is happening that will be embedded inside the system. It is not now controlled by the human, but allow the human to see what's going to happen in the system before it happen. So it is more or less a prevention and supervision that will be embedded into that application inside the system, which we call smart system management process.
Wow.
[00:31:30] Speaker A: Yeah, that seems pretty complicated at this point I can see where there's a lot of training involved. So like in education, how do you ensure AI enhances learning rather than replacing critical thinking?
[00:31:44] Speaker B: Well, let me give you a real example.
About a year ago we started using actually different application of AI in the classroom.
And one of the session that we have, we have one individual in the classroom, we have about 60 individuals in seat. He asked the question, can I use ChatGPT to do my homework?
And I said yes, you can.
Perfect. You can use ChatGPT and you can create the algorithm that you want. But when you created you to come to the blackboard and explain to me what you did there.
And he said ah, you mean I have to tell you how I did it? I said, well that's the main idea for you to be sitting in this place to think you can use it, but you know how to use it and what is the limit of that use? And you have to demand, train the people how to use the application, but demand from them that they need to apply it in a proper and biased way. That is the only way how you can prevent them from using technology without thinking. Because technology is very dangerous if you don't know how to use it.
Like if you are going to drive your car, but you never drove a car, you are going to crash one way or another. Technology is the same, so you need to use it, but use it in a way with principle. I would say like in our case with Christian principle, that mean protect the infrastructure, use it in the proper way, don't be biased, do the right coding system, protect the environment and protect the infrastructure by using the proper application of artificial intelligence in it.
[00:33:35] Speaker A: Yeah, that's. That seems like extremely important. Especially with guys on the job who are just get lazy and just throw it into chat or AI. You know, we gotta make sure that they don't do that. So is a potential, is AI potential threat to humanity or does the risk emerge from misuse and lack of governance?
[00:33:59] Speaker B: Well, it is, it is actually an obstacle. But as we said before, it depends on your mission, on your objective and who you are going to have working in that application. If you have ill people working in that application and they called it to their benefit to destroy something, then that is actually very dangerous. But if you train your people and put your policy in place, crystal clear policy of artificial intelligence, that governance policy will work well and then you protect everyone at the same time. But you need to have a good understanding of it and more or less have it at the executive level so you can protect the infrastructure and be liable to what you are doing.
[00:34:46] Speaker A: Excellent.
Okay, so up next time, the future of AI, the future of work and what leaders must do now to stay ahead. Stay tuned.
And we're back. I'm Jim Bradfield and this is ever changing technology here on Now Media Television.
This is ever changing technology on Now Media Television. Watch anytime on the Now Media Television app, available on Roku iOS and Android or stream at www.nowmedia.tv.
let's close by looking forward.
With every innovation, something old must be left behind.
What must we evolve next?
Dr. Hakim, as AI is AI a potential threat to humanity or primarily a tool for advancement? What determines that outcome?
[00:35:48] Speaker B: Definitely it's a tool for advancement to help human make better judgment and solve real world problems.
Artificial intelligence, it is not a threat to humanity. You need a human to make a decision on the outcome. It is very important to understand artificial intelligence. As we discussed at the beginning, when the Chinese start building the wall, they needed an instrument. We have a lot of data today in the market. We as a human, we cannot work with unstructured dark data.
We need artificial to help us so we can make the proper decision and make a decision based on the data collected. That data come from artificial intelligence and then we can make real information and understand the information that we have to apply. But in no way artificial intelligence is threat to humanity. Actually it is an excellent tool to help human live better, have better environment and have enough time to solve the problem in due time. So there is no way that we should conceive artificial intelligence as a threat. It's our help. It is like if you have somebody working for you, that does not mean you are going to leave that individual alone and leave. So you are going to work with that individual. Consider that as a help, that is your assistant, that is your partner to do something to create a good atmosphere, to work together and contribute so you can do better job. It's for the benefit your Job will be more efficient and the outcome will be much positive. So there is no way that we should classify it as a threat. We should be happy to have a tool to help us. I am happy to actually go from one place to another and fly in an airplane. I don't want to go and horse ride from here to California, it'll take me forever. I want to just ride on the plane. That's a tool for me.
And I'm actually, I'm not staying one year to go to California. I will go in two hour and a half.
So artificial intelligence, we should think of it as a great tool. We should embrace it, use it. But we need to understand how to use it and put policy in place to protect from ill use. Artificial intelligence is the best that can happen to humanity.
[00:38:09] Speaker A: Amazing. Yeah, I agree with you. Now how should universities and corporations redesign their training programs to prepare for AI driven roles?
[00:38:20] Speaker B: Well, in the university, at the level of academia, we try actually to help the student understand the process, the technique and the application.
Like we discussed at the beginning, that individual that came to me and said can I use ChatGPT? Yes, you can use ChatGPT, but you need to understand that you need to let me know how you did that.
So the individual going to any of those measures, they need to understand how to use the application. We prepared the student to face the challenges of the future. We give them the tool, the technique and the lab so they can use it in seed. And when they go to the industry, they can use that tool directly. Day one on the job the most important thing is to know how to apply executive they need to know what they need and how they use. But individuals that work for them, they need to apply and use the proper application to solve a real world problem. So we teach them actually the process, procedure, step and application. So we prepare them for the future in their job. That is how we do it in academia. We don't just give them a lot of paper to read and go and do homework and come back and tell us that they wrote a good, good 20, 30 pages and you say what garbage did you give me today? How that is helpful to me?
Give me something that I can use to benefit me. And that's why you prepare, you go to school to use your knowledge to solve problem. Right. So if you don't teach your student the proper technique, tool and application of the same and know how to do it, then you really are wasting your time. Don't go to school.
[00:40:10] Speaker A: Right. Okay, so having said all that, what does quantum computing Intersect.
Where does quantum computing intersect with AI and and, and why should leaders be paying attention to that now?
[00:40:23] Speaker B: Well, quantum computer, it is the future of application and to solve human problem in a fast and critical way. Quantum computer is it used the domain of quantum physics.
And it has three characteristic quantum physics that will have also computer science, electrical engineering and mathematics.
Those domain getting together into quantum physics, what we call quantum machine learning.
Machine learning actually will learn from the pattern and make prediction faster and more precise than artificial intelligence that we have right now. As we discussed before, we are in the era of broad AI. But when we come in the general AI that what we have quantum computer and we can make better prediction, faster, more reliable. And it is what we have problem right now in understanding through machine learning and machine reinforcement learning. Then in quantum computer it's going to be much easier for us to understand and process the information and in very quick time. To give you an example, what you do right now in one year in quantum computer, you can do it in probably three minutes.
So that is the idea of quantum computer is the prediction, the precise prediction of that outcome. That's what we are working for, that's what we are trying to achieve, that will have better prediction. And instead of going to the doctor and say I have pain in my heart what you can do, I don't know what you have. But when you have quantum computer now, you have better prediction, faster prediction and the data that is being scrutinized in that time, it's going to be analyzed much quicker and much better.
So that is what machine quantum computer does for the humanity in few years, I hope.
Great.
[00:42:29] Speaker A: So you know, you mentioned this earlier, I think but the governance model should organizations implement to ensure ethical AI use is what?
[00:42:41] Speaker B: Well, to implement it first you have to have in place policy, general policy, crystal clear to the individual. Now for you to implement a policy, you need to have your mission and your vision crystal clear in your mind.
And once you have that, you understand what you are going to accomplish. Now you can implement artificial intelligence, use an application in your workplace and government will use it. Actually it's very important like quantum computer for national security.
Because if I have a threat, I'm not going to wait 10 minutes to find what threat or what missile is coming to me. I will find it in second and protect national security. That what quantum computer will do for you, its quick prediction, precise prediction and accurate prediction. As you remember what we discussed on augmented intelligence, we have that the machine will ingest amount of data and make a repetitive processes accurately.
Now in quantum computer, now that you have quantum physics, that means it's operating at very, very, very low degree, which is less minus about 270 degree centigrade.
And that is actually very cold. That means we'll process the data much quicker, precise and give you accurate protection of that missile coming to you. That is for national security or world security aspect. But quantum computer is actually the new technology and innovation that is coming on board very, very, very soon. And we have a lot of company working on it right now.
We have IBM that they start putting and working on quantum computer.
We have Google, that is we have another company that has actually made good stride in quantum computing. They start testing it in London and they have good prediction. And now they are coming at the precise prediction to predict what will happen, what outcome they will receive. Actually what we are looking between 99 and to 100% prediction rate.
So quantum computer is very important to apply and this is the future of artificial intelligence.
[00:44:54] Speaker A: Awesome. Okay, so we got about a minute left.
Give us a point A to point B. Roadmap. What are the three immediate steps leaders can take? Just please summarize them for our viewers.
[00:45:07] Speaker B: Okay. The roadmap is very important. First, for you to apply artificial intelligence, you have to make an internal audit of what you have in place at all level of your organization. It doesn't matter if academia or any other organization.
And what you will do is you will find, most definitely you will find that people that are using artificial intelligence right now in your organization and they are using not approved case scenario and there is no risk tolerance. Watch for that one. So what you do until you do that internal audit of all your technology resources and see what's happening there, then what you can move to the next step in those 30 days and put a policy in place, artificial governance policy to protect your institution or protect your organization. The second one, you adopt two to three case scenario and that will be a pilot program that you will work with to see how it will work in your company.
And then you put a risk tolerance there. And the most important thing when you apply that, you have to put risk management, combine it actually with application and compliance and make it at the executive level so they will know for sure that they are going to be facing the music if something went well.
So that is the step by step, actually general step to implement artificial intelligence in less than 30 days.
[00:46:39] Speaker A: Awesome. Dr. Hakim, powerful insights. Where can viewers connect with you and follow your work?
[00:46:45] Speaker B: Well, actually they can look at our website, at the university website.
It is Zhaikemc Edu and they are welcome to send the information actually to you and you can send it to me or the tv, media, whatever. I will be in touch with them. But I will welcome the opportunity to answer any question and help them navigate through this new technology that we have.
[00:47:13] Speaker A: Awesome.
Wilson, we really appreciate you being on the show and I'm Jim Bradfield. This is ever changing technology.
Only on NOW Media television.
[00:47:25] Speaker B: Thank you.
[00:47:26] Speaker A: It.
