Transcript for episode 73

Gretchen Huizinga: My guest today is Joanna Ng. She was formerly the head of research and the director of the Center for Advanced Studies at IBM Canada, and over the course of her seven-year tenure there, attained the title of IBM Master Inventor because she holds 49 patents, has published more than 20 peer-reviewed technical papers and has written two computer science research agenda books.

She's now running her own AI startup, focusing on augmented cognition assistance, and has just published a new book called Being Christian 2.0: Instead of Losing Heart, Let's Start Over. Joanna Ng, welcome to the podcast.

Joanna Ng: Thank you. What an honor to be invited.

Gretchen Huizinga: So as a level set for the rest of the interview, and because you're the first guest on this podcast who not only knows how the sausage is made, but you've actually made it, tell us from a technical insider's point of view: what is AI today, and maybe more importantly, what isn't it?

Joanna Ng: Okay, so let's put it in the proper perspective. Artificial intelligence started in 1950 when Alan Turing published a landmark paper called "Can Machines Think," and that devised the Turing Machine, using humans as a benchmark to conclude if machines can think. Turing did not coin the term AI. In 1956, in a summer conference in Dartmouth College, there was a workshop in the conference with six researchers from MIT and Carnegie Mellon presenting, and basically they were presenting the work of AI and that's how, out of that workshop, in that conference in Dartmouth College in 1956, the term was coined. These six researchers coined the term.

They defined AI as the construction of computer programs that engage in tasks that are currently more satisfactory performed by humans because of their higher-level mental process. So some examples of higher-order brain functions include these tasks such as speech recognition, computer vision, natural language processing and generating content as we know it.

So, let's talk about what AI is not. AI, like other technology, is a tool created by humans and used by humans. there is nothing mythical about it other than how Hollywood wanted to mythicize it. Fundamentally, in the bare bones, it uses mathematics and statistics to derive abstract models from data being fed and uses the models to do predictions and projections. That's it. It's all math. Many scientists and technologists from the field who know AI all agree to say AI is not intelligent at all.

Kate Crawford, a professor in Southern California and also a researcher in Microsoft, lately published a book in August of last year called The Atlas of AI. She basically says AI -like the rest of us who are in the field - says AI is not intelligent because, for example, it can only do correlations in statistics, which is how the data relate and the patterns relate, but it doesn't do causal analysis. It can never answer why. It cannot do common sense judgment. And it totally depends on the data. We don't call out the biggest flaw of it all, which is the absence of absolute truth, because whatever is the truth is in the data.

So I'll give you an example why that is so flawed. So one project, I did with U of Maryland was to process the medical data from a couple millions of veteran health data in the database. And everyone was normal from a high blood pressure point of view, because 95% of them have high blood pressure. So if you have a blood pressure of 165, you are normal. Whereas in Canada, they ask you to call 911. Okay. So that goes to say, in the absence of the truth, what is considered normal as blood pressure is anything lower than 130. In the absence of that truth, the truth lies in the data. So therefore, 95% of people having a blood pressure of 165 did not make it not high blood pressure, even though norm is high blood pressure.

That just goes to show why it is not intelligent, because of the incapacity to handle independent truths. Okay?

Gretchen Huizinga: Yeah.

Joanna Ng: And let's talk - one last point is about affective computing, which is the AI science on human emotion. So far, it can only detect human emotions, of course, with lots of biases. Like if you throw in a different culture, it wouldn't be able to detect it.

But it can never elicit emotions because emotions come from the deeper being. So, the mechanism of why seeing a ribcage baby from Africa would bring tears to humans as emotion is because of the human's capacity for compassion. And you can make an artificial association of certain pictures with creating sadness, but it doesn't come from a deeper force.

So that's to put AI in this proper place. It's overdramatized.

Gretchen Huizinga: Right, right, right.

Well, I love that you brought in Kate Crawford's book. I've read that too. And one of the biggest questions, or I would say problems, with AI is because it's not intelligent, but it can trick us, because it's so good at some of the things that it does that it makes us think there's understanding behind it or cognition and so – and this gets back to Turing also in the famous Turing Test – could we believe that an AI is intelligent? And so there's that funny little interstitial space where it's like, "Okay, it isn't, but it seems like it is, and it will fool a lot of people, so we go ahead and call it intelligent." We could go on an entire podcast about that. Let's not.

Let's, let's talk a bit about this, what I would call an inevitable march in some people's minds toward Artificial Super Intelligence or ASI. Some people call it AGI, which is Artificial General Intelligence. But that's actually different. The Artificial Super Intelligence is what you sometimes call the "singleton."

So, in 2020, Christianity Today published an article you wrote where you compared ASI to the Tower of Babel in Genesis 11, and you argued that we shouldn't spend time pursuing it.

Joanna Ng: Yes.

Gretchen Huizinga: Even though lots of people are, why Joanna, should we not, and what should we be doing instead?

Joanna Ng: So, ASI is the level of intelligence with the goal that it surpasses humans. So, if you run the Turing Test, you have the machine and the human doing the same thing, then the machine will always be superior. Okay. So that's the singleton. Compared to, in AGI it's equal, which is the goal of the Turing Test, which is you both play chess and you cannot tell which one is which.

Gretchen Huizinga: Oh, that's a really good differentiation because I was sort of conflating the two. And it's like "as good as, or, better than."

Joanna Ng: Right, and when we are not even AGI. Right.

So, there is a 2016 study that, based on their data, they project that there's a 90% chance that we'll reach AGI by 2075. I probably wouldn't be around to see them wrong. And 75% would project, that there's a 75% chance that it will reach ASI by 2105, by which I'm absolutely long gone, I hope.

So the core question remains: is ASI a function of time or a function of nature? I tend to think it is a function of nature because it goes back to your core belief of what is human. So, I believe the human is a body that has a soul. The soul includes your mind, your will, and your emotions; that has a spirit. And the spirit connects with God when you reconnect with God. Right? If that is my view of humans, then so far AGI was aiming at replicating the mind. So far AGI only tried to replicate the mind, and one has ever tried to replicate the spirit, or even come near to it. So that's why I assert that ASI is a function of nature, because no matter how hard you try, there is a limit in terms of the spirit, I believe, is not replicable; the mind- some parts of the mind are, you can externalize it, and are replicable, but not the total of it because the mind connects the spirit, the spirit connects to the mind.

And so that's why I say instead of pouring all the scarce resources of AI to attain ASI, which I personally believe is a sunk cause, because I believe ASI is a function of nature, then you have a huge opportunity cost, which is to apply the advancement of AI for the benefit of humans. That is a huge opportunity cost. So to put it in a proper perspective, I said that the AI field started in 1950, okay? Based on those projections, one would ask, would 155 years, to 2105, be long enough for a human- created intelligence to be superior than human intelligence created by God? I don't think so, and that's why I call it the top of Babel because, it's always the human attempt to surpass what God created man to be. Right? Which is also the essence of the Tower of Babel, to be like God.

Gretchen Huizinga: I agree, and I think there are other people that don't, and maybe it is anchored in worldview. If you believe that we've evolved from nothing to something, and then if we just keep applying time, soon enough we'll be at a different level.

So yeah, this is another thing we could do an entire podcast on, and argue -

Joanna Ng: Yeah. And to interject, right, so Kate Crawford in her book says that the biggest mistake computer scientists ever made was to equate the human mind to machines. And that presumption led us down a very wrong path.

Gretchen Huizinga: Well, regardless of whether we're ASI, AGI or whatever, we have seen some amazing advances in what we call AI recently and particularly in the area of Generative AI, and this is where it gets a little weird. First it was image generation with the DALL-E's and Midjourney and Stable Diffusion, and the most recent buzz is around the language generation, particularly with the recent announcement of ChatGPT, OpenAI's language model, which some people are calling "the calculator for writing."

Aside from all the immediate questions that these AI applications raised for people in say, art or education, I think there's a bigger question and I want to ask it to you. If AI was supposed to automate menial tasks so humans would be free for creative pursuits, say a human-only domain, what happens when AI seems better at those activities as well, and what does that mean for humans, then? Kind of tying back into your last answer.

Joanna Ng: Yeah. So humans are able to create because we are made in the image of God, because God is a creative person. So in the creative process, we often experience what we call the flow, the creative flow state. And that creative flow state interacts with your spirit and your mind. That part can never be replicated. The mental state of being completely immersed, that you receive intuition, or even, for some of us, we can receive divine revelation, that part of the creative process never be duplicated.

However, generative AI refers to the unsupervised or semi-supervised machine learning algorithm in order to generate new data that follow all the boundaries of the model of the real data. So, that's why it makes it believable. But we are able to know the difference because, like what I said before, AI can never have causal analysis; AI doesn't include the scope of absolute truth; AI cannot elicit emotions... So the best it could do is to synthesize data. Like if you want ChatGPT to write a proposal, it will pull information from multiple sources and synthesize it. But it still lacks that spirit of the sizzle, may it be the insight, may it be the understanding, it be the absolute truth, or may it be... AI is still limited, or not able to think in the first principles as humans can.

So, generative AI can be a great companion to evaluate and to verify or to synthesize, so that we don't have to do all that research. But the insight comes from a human, and so the best of generative AI is to use it as a companion, as a collaborative - accelerate your creative process. But light bulb comes from the deeper part of the human, that sometimes can't be explained.

Gretchen Huizinga: Well, because you are who you are, I want to talk a little bit about how technology moves from theory into practice, or from the lab to the market, as some people say. And it used to be called "tech transfer," where universities and companies would have research departments and they'd say: "How can we make this a product?" "How can we monetize this?" So, as somebody who holds no patents whatsoever, I'm intrigued that you've been awarded 49 of them for your work at IBM, and I also know that you're working on applying for some now for your new work. Could you talk for a minute about the process by which research becomes business and the role that patents play in that area?

Joanna Ng: So, first I'll talk about research becoming business. Being hired as the head of research in IBM Canada, my mandate is to take research outcomes to commercialize into products. So that's why IBM Canada at the time did not pick a pure academic to head the organization because they didn't only want the academic part, but they wanted the academic part to be able to commercialize into products that can be put into the customer's hand that solve real-world problems.

From research outcome to commercialized product in a user's hand is a very long journey. It involves many different stakeholders and it's one of the – so, during the seven years of tenure, my mind was so stretched because there is a science front and there is a commercialization front. On the science front, you need to understand what is the advancement of science that the paper articulates. It often, as anyone in research, especially pure research, would tell you, that the advancements of science do not relate to anything. Right? You know, someone comes up with a – Turing, comes up with a finite state machine – “Who knows? You know, it's kind of cute, right? Like, who knows what this is used for?"

So, the key to understanding the technical potential of a research outcome is first, but that's where the academia stops. The mandate that I was given as the head of research for IBM Canada is industrial research, because I was told my mandate is not to stop there, because the executive will quickly figure out: I pay all this money and I have 40 papers published – where's the money coming from? Where's the return on the investment? So it cannot stop there.

And so the second link, then, is to take the research outcome, understand the technical potential, and be able to see the potential of application in the solution to a real world problem. That's the science part.

Gretchen Huizinga: Okay.

Joanna Ng: So once that's done, then there is a commercialized front, which is: is there a value add in this product that the customer is willing to part with their money to have? And that has nothing to do with the science because - the earlier part of my seven years, I brought too much of the science into the commercialization front and it didn't come across well because basically, at the second stage, all you care about is: how does it make my life better? And you lose all the complexity of the science, versus the first one. But you cannot, not without the science, because the science is your credibility, right? Like the due diligence that if you apply this correctly, it did work, right?

And so, it goes from a range of being a deep-dive technologist, to losing all the detail and coming over and saying it in one sentence, while you had years of work to make this happen. And you have to swallow your pride and say, swallow it and net out the last five years of research outcomes into one tech line so that the marketing guy would say, "I know how to sell it." And that's a long journey. So, that's the journey. Okay.

Gretchen Huizinga: I love it.

Joanna Ng: From science to commercialization is that journey.

Let's talk about the role of patents. I did not start out wanting to be an inventor. I did not start out wanting to be a patent collector. I purely enjoyed the process of taking research outcomes to commercialized products that can be put in the customer's hand. That process initially was painful, but at the end it's enjoyable. And so I completely enjoyed that process.

So, how I ended up filing so many patents? The first go around was the IBM mobile commerce product. I worked with the IBM research and did all the work and we were ready to ship and the senior executive stop ship my product. And I was so upset because, you know, I told you the journey of taking the research outcome to productize is a very hard-earned process. And when it is now ready to be birthed, it was stop ship.

And this is how it was explained to me: that it was stop ship because the innovation inside was not protected. And if our competitor produced the same novelty in their product after us, and if we don't have a patent, they can sue us for royalties, even though we were the first. So if I ship product without filing the patent, then our competitor could come after us and know that we don't have a patent see that we have similar features, they can come back and sue us and there is no protection.

Gretchen Huizinga: Would that mean that they had filed the patent?

Joanna Ng: Yeah.

Gretchen Huizinga: Because they can't sue you if neither one of you filed a patent.

Joanna Ng: Right, right. So that's why the executive stop ship my product because if I don't file the patent, it would do the company harm because it's up to be sued if our competitor filed the patent and we didn't.

So I was kicking and screaming. I was like, "I don't care. I just want this to be birthed!" And then once I understood it, "Okay." And in that one product there were eight patents being filed.

Gretchen Huizinga: Wow, eight?

Joanna Ng: Eight. So just for that one product, there were eight patents being filed. And so that started the journey and then thereafter, it just keeps coming as long as you keep working. So, patents are to protect the right for commercialization for the first mover, and I learned it the hard way.

Gretchen Huizinga: Right. And I guess if you extrapolate downstream, it would also protect you against other people coming in without a patent, using that stuff and saying, "we get to make money." And you say, "only if"- well, how does it work? Do you have to pay? Can you still use it, but pay the person who has the patent, or can you not use it at all?

Joanna Ng: So whoever has the patent has the commercialization right. So anyone who doesn't have the patent and wants to use it will have to pay royalties. In IBM then, the patent royalties paid by everyone in the industry was close to 10% of our earnings.

Gretchen Huizinga: Wow. Oh, that's significant.

Joanna Ng: Yes, very significant.

Gretchen Huizinga: So patents are protective and good.

Well, okay, so without giving away any trade secrets, let's move on to what you're working on now. You've moved from working for IBM, which is a major tech company, and now you're doing startup work, which is fascinating. And your new work is focused on augmented cognitive assistance. You call it AI for Me. Explain AI for Me, without giving away any trade secrets, so that you can't get sued. How is it different from AI for everyone and why would I want it?

Joanna Ng: Okay. So, AI for Me is an obvious deviation to live according to what my assertion was, which is I do not want to invest the remaining days of my years to pursue ASI, and because of that opportunity cost. I want to use AI to benefit people. And AI for me is that space.

So, AI for everyone is the apps we use today, right? Like, the apps you use and the apps I use are the same, right? and it uses general algorithms and public data to give you services that are of your concern, right? So that's AI for everyone.

AI for Me applies AI to my personal data with the goal to augment my cognitive capacity and reduce my cognitive load on what I care about. A more formal term is called "augmented cognitive assistance." And the improvement can be measured because you can measure with or without it, right? And the improvement is called the augmentation factor; we call it A+. The timing is right because – later on we'll talk about Web3 – with the focus on personal data, it totally adds a different edge the new web that we wanted to redesign.

Gretchen Huizinga: Hm. Okay. Let's go there because this is an interesting intersection that a lot of people don't understand. When they hear "Web 3.0," they probably couldn't describe what it was unless they were involved in technology. But to put it in simple terms, it's kind of a massive decentralization of the internet, Web3.

So, some of us may know what that's about a little bit, and others may not. Can you give us a bit of education on Web3 and how technologies that underpin it, like the blockchain, in addition to AI, will change our lives in the future? And maybe tie this into your AI for Me, because there's a little bit of that in Web 3.0.

Joanna Ng: Yeah. So if we think of the web like a car, the first car can only drive from one block to another, and then you say, "Oh, if I want to accelerate by five miles an hour, I have to do five actions in the shift stick within two seconds. And that's like, "Wow, why don't you come up with automatic transmission?" and then eventually now like, "Oh, can we not use fuel in the car" and therefore you have the birth of the electric car. So, if we think of the web kind of like the car, we'll understand.

I published the book called The Smart Internet in 2010, and then subsequently, I, together with other professors, published another book called The Personal Web in 2013. I basically led the research team, with the professors from various universities from Canada and some universities in the States. I basically put out the question; I said, "Why are we happy with the internet? If I ask you a question, I expect an answer. But if I ask Google a question, you give me a bunch of links! Why should we live with it?" Right? And that's how the project got started.

Web 1.0 is a read-only map web, which is only html. Web 2.0 is an interactive web with a centralized platform. We know, the site we interact with, the platform's owned by them, right? That's why it's very different from productization in that, like, Facebook never gives out their platform. Any of the big tech, Google, any of the big tech would never give out their platform. So it is interactive, but it's a centralized platform with big corp, big tech, and big enterprises. That's Web 2.0.

Now, in my book, The Smart Internet and in the book The Personal Web, I did call out all these problems. That was 10 years ago! And so it's the same in that, number one, why do these big enterprises control everything? Why are they the bully? Why do I have no say that my data has to be given to them? Why do I have no control on my own data? Why does Facebook dictate how my information is being published? And so Web 3.0 is basically saying, "Okay, we've used the internet long enough and there are so many things we don't like about it; let's fix it." It's kind of the big umbrella of that.

Now you have to understand, I'm dating myself. I lived through Web 1.0 and 2.0. Okay? So in those days, to be able to, in Web 1.0, able to display the html file, we high-fived each other. In Web 2.0, when the first object from a database could be transmitted from one end to the next (that was only 500 bytes), we high-fived each other. So that's where we came from. It's just like if a car runs, and it's not a bicycle, goes from one block to two blocks, we high-five each other. That's the car version. So internet is exactly like that.

And that's what prompted me to publish the books The Smart Internet and The Personal Web, because it's been 20 years, then, it's 30 years now, and we are still at the bare-bones function. There's so much more that's wrong about it.

And so basically Web 3.0 is a big umbrella term to fix whatever we don't like. And then what you don't like, there is a popular view and there is a more a silo view.

So, for example, one thing we don't like about the web is that it is being monopolized by the platforms. So that's why you see decentralization. The DOA, the decentralized autonomous organizations, the Blockchain and Crypto become the key thing because we know that we don't want the big platforms to be the war lords of the internet. And that's why decentralization is a big theme. But we cannot lose sight of the fact that at the same time, when web 3.0 is birthing and no one has an autonomous claim on what Web 3.0 is, it's what we want to make it to be: to fix Web 1.0 and 2.0.

So without losing sight of 5G, AI and Internet of Things totally change the world. If you apply that integration, then you really can have a really, really smart home.

Web3 is really fun right now, because we know – that's why, people like me, even though I'm not a third-year dropout from Stanford, I claim that my contribution to Web3 is because we are part of the team that made all the mistakes in Web 1.0 and 2.0 so it's now time to say, "Let's start over. We can make Web3 really cool."

Gretchen Huizinga: And that phrase you just said is going to lead into my next question, but I want to stop for a second and say, one of the reasons that I have resisted having a "smart home" is because I think I'm giving away my privacy. I'm even afraid to talk in front of my phone sometimes. But this Web3 and AI for Me would hopefully resolve some of those fears of invasion of privacy and "What is someone going to do with the data if it's not anonymized," et cetera.

 But, I also know that when the internet was invented originally, It was invented for the military so people could talk - it didn't have this vision and it's morphed into this thing. So the idea of fixing it or patching the code, to use technology terms, versus starting over is an interesting question.

So let's talk about the new book you've just published called Being Christian 2.0: Instead of Losing Heart, Let's Start Over. And I want to say I love your book dedication, because you say, "Version 1 is no longer supported. Fixes to bugs will only apply in 2.0. Please upgrade." So, what does software versioning have to do with the Christian Walk, Joanna?

Joanna Ng: So, in the software world, if any product releases minor fixes, they are called releases. So, you have 1.1 and I'll give you a new release with minor fixes. That's 1.2, 1.3, right? So these are minor fixes. When major fixes are delivered, either because there are fundamental technology changes or new architecture, we reversion to signal to the customer that this is a totally new level of product. So, that's the reversioning instead of new data releases. So that's where it came from.

So when applied to 1.0, 1.0 of my being Christian is purely operating in the natural realm. There is nothing supernatural about being Christian. Man thought, "Oh, it's purely performance-based. It's basically trying to do good, on my own terms, according to my understanding, and that's it.” So church volunteering is a big deal, because that's how I learn that "Oh, people who love Jesus volunteer at the church." So I volunteer at the church to the wazoo, right?

And, so sooner or later it crashes completely because there was no Holy Spirit. "Well, I'm sure he's there, but I just kind of do not bother him." And it doesn't go deep in the Word. And there is no demonstration of the power and the authority of Christ. And actually, in Timothy 2, there's a verse that that's a form of godliness, the void of the power. And that's a good description of being Christian 1.0.

So 1.0 of me is trying to use my own effort based on human understanding, that is mine, to be a Christian for God, regardless of what he thinks about step 1.0. Okay. And it crashes because sooner or later you run around empty. There is no sense of purpose. There's a no sense of a higher calling. There is no sense of relying on God, trusting in his power. So, it needs a major fix so that you press the reset button and go to 2.0.

And 2.0 is very different. 2.0 is about letting God glorify himself through my surrendering to him and letting him do immeasurably more based on his supernatural enablement of me that people can see and say, "It's not Joanna, it's God in Joanna." And that's difference.

Gretchen Huizinga: Got it. You mentioned church volunteering in that, and I know that that's a part of your book and in the gospels of Matthew and Luke, Jesus tells a parable about a shepherd who leaves ninety-nine sheep to find one. But in your book, you have your own ninety-nine-to-one ratio story, but it's got a little bit of a different twist. Tell us what it is and why you think it's essential for churches in version 2.0 of being Christian.

Joanna Ng: Okay. So for those of us who are still in our being Christian 1.0 days, we think going to church on Sunday morning is being a good Christian. And if we watch our language, it implied that we see Church as a religious institution with a building. That's not what Jesus meant about Church.

If you look at Acts and see how Jesus spent his last 40 days. How he spent his last 40 days on Earth shows you his priority, doesn't it? And if I were him, worried about how to build the Church institution until he comes back, in the remaining last 40 days, I would make sure I picked the best CEOs and gave them the classic Church Constitution, to govern the Church such that the organization of the Church would keep running thousands and thousands of years until I come back.

He did none of that. None of that. He spent the last 40 days on earth to talk about the kingdom of God. So that just gives you a sense of his priority. So he's not here to build the Church institution. He's here to build the Church as his people. So instead of saying, “I go to church,” we should have said, “We gather as Church, we gather as his people,” because Jesus didn't die for the institution as church, Jesus died for his people as Church. Sometimes we often fall into the trap of building the wrong Church. We spend so much time to build the mega church, the franchise church, the religious institutions, the denominations.

They turn out to be only the earthly kingdom built by man. That's not the kingdom that Jesus wants. Church is Jesus' people. And so Jesus is the head. So, most of the problems of the Church – I've talked to many churches and they unanimously, a lot of them told me, "Oh, my biggest problem is finding church volunteers."

And I'm like, "That's not your biggest problem." To see members of the Church as resources and utilities for the building of the Church as a religious institution is not what Jesus had in mind. Jesus wants his spiritual leaders to see his people as Jesus' sheep and trust it to be fed and trust it to be brought up into spiritual maturity. And that is fundamentally missing. And therefore churches need a 2.0 for that purpose. So many churches are run by executive leadership, but there is a scarcity of spiritual leadership. If we are not guided by the Holy Spirit, we are disconnected from the head of the Church, which is Christ.

So the problem is that many Christians are not being built up spiritually and do not know our calling. They don't even know that they have a calling. They do not know why Jesus put them on the front line of the world. the 1% is called by Jesus to build up the 99% in the full-time industry, and the 99% would be mature in their calling as they are being called to the various front lines in the world. And so the shift needs to happen, which is instead of seeing the Church as a building, as the playground, we should see the Church Institution as a training center to train people. Instead of seeing the 1% as the players of the kingdom ministry, we should see the 1% as coaches of the 99%.

Gretchen Huizinga: Wow.

Joanna Ng: Instead of seeing the 99% as volunteers or spectators, we should see the 99% as the key players in their playground, in the front lines of the world. So that's the church 2.0.

Gretchen Huizinga: Aside from your work in AI and your writing, which is a big chunk of your time, you've also founded a ministry called KOE. Specifically, your heart is for Christians in high tech, which, as any of us know, is a hostile environment, often enough for followers of Jesus.

So what does KOE stand for and what's its purpose, Joanna?

Joanna Ng: So KOE stands for Kingdom on Earth. The real kingdom of Christ only has one version. And the primary purpose is three things: to awaken, equip and support the 99% not called to full-time ministry but called to the front lines of the world.

It is to awaken to the 99% that God has a divine assignment for each of our lives. That's the first awakening because it's not possible to live the in the fullness of life Christ died for us to have without knowing our purpose.

The number two is equip. The first is A - Awaken. E - Equip. Equip is to equip them spiritually so that they mature and have the spiritual competence to be Christ's priest, where God strategically situates us in the specific front line and created us for such a time as this.

The third is support. Support the 99% in the situations that the local Church is not equipped to support.

So I'll give you an example. Last week, 40,000 workers in the tech industry have been laid off. That's a fact. Many are in the tech Christian prayer group. We need priests in the industry, mature Christians in the ministry to minister to people in the tech domain for such a time as this. Because we understand the culture, we understand the toxic elements, we understand what happened, and it is kind of unfair to us, the 1%, to understand enough to minister to. Right. And that's what KOE is for.

Now, every industry has this stuff, right? So say, lawyers, I know a bunch of lawyers, they have their own support group, so that when legislation that is against, the biblical teaching, they would gather enough of a voice to say it. Other industries should have their KOE group. Like businesses, like how can we, be different, to be anti-greed in the business, in the finance world, right? Like, how can we not speak up when the greet would collapse the entire, market, like the 2008 crash. Where the heck are the Christians? Not saying anything, right?

So, that's what the KOE is for, it's for awakening, equip and support.

Gretchen Huizinga: And so you have a specific call and vision for the tech community. And it's interesting because, when you talk about the 1% of priesthood or the professional priests as we've made them across Christianity. I mean, there's some denominations that call them priests. Others call them pastors or ministry leaders or whatever. But what you're proposing here is this, as you say, democratization, which takes a burden off of a small number of people, including the fact that lots of people in tech aren't going to go to a church.

Joanna Ng: No.

Gretchen Huizinga: So they won't never have a chance to interact with a professional priest. The only priest they'll ever interact with is somebody who's placed in their workplace.

Joanna Ng: Yes. And if we say Church is not a building to go to, nor a membership of an institution, and if Church is as Jesus meant it, "gather as people," I have Church in the tech community.

Gretchen Huizinga: Right.

Joanna Ng: When I need to make a tough decision, I know who to call, to pray for. And they pray with understanding because they're in the same field, right.

Gretchen Huizinga: Yes. And that's key. I love this.

Well, we could go on forever and I would actually like to, but we're closing in on time and at the end of each podcast, I like to give my guests a chance to share some of the books that have influenced them, whether they're professionally or spiritually, or both.

So, Joanna, as we close, what are two or three books that have made an impact on you, and why would you recommend them to our listeners?

Joanna Ng: I'll list four, okay? I'm going to sneak one more in. Okay. So the first book is How to Read the Bible for All Its Worth by Gordon Fee. This book is awesome. It grounded my spiritual gift in the Word with a solid framework to understand the Word that helped me from twisting the Word in God. So this is the number one book. It totally is very fundamental to my faith.

The second book I recommend is The Art of Listening Prayer by Seth Barnes, published in 2004. And this is another book that is very important in my faith journey because it guided me to the discipline of listening to the voice of Christ through the Holy Spirit. The Art of Listening Prayer.

The third one is Boundaries. Henry Cloud and John Townsend. The first edition is 1992. There is a new addition in 2017. It armed me with the tool to learn to love myself enough by giving me the permission to say no to others. I advocate that every high school should make that a mandatory reading.

Gretchen Huizinga: Boundaries.

Joanna Ng: I really recommend that. Then the fourth one is also my lifesaver. The fourth one is the book called Originals: How Nonconformists Move the World by Adam Grant. It was printed in 2013. So it validated my long journey as being the odd one in the crowd, and allowed me to accept myself, and gave me energy to persevere, through the many, many rejections are inevitable for anyone trying to do anything original. It gave me the bonus to continue to pursue my dreams that are often rejected by others, without giving up. Originals. And I realized, "Oh, okay. So I'm not that abnormal."

Gretchen Huizinga: Right! I've actually met Adam Grant at a conference.

Joanna Ng: Oh, wow.

Gretchen Huizinga: Yeah. And he gave a talk and he's a really cool guy. Really, really good.

Those are great recommendations. Are there any in the tech space that formed you? Or is this – I mean, that might be technical books that only people in computer science would be reading and getting ready for learning to code and things like that.

Joanna Ng: Mm. Okay. Well, the Reinforcement Learning textbooks, I might have it right here somewhere, are pretty good. Design Patterns is another very good book. Design Patterns is a very good book, because if you want to be good in your trade, you need to learn to take the mass – you need to think in abstraction from the raw data.

So I learn over time that, I thought everyone was thinking in abstraction, until I realized –

Gretchen Huizinga: No, we don't!

 Joanna Ng: So, if you want to do your trade, because everything comes from proper abstraction from details. So once your model is right, then innovation happens with the model. So Design Patterns by Eric Gamma and Richard Helm is a classic book.

Gretchen Huizinga: And that's a lovely way to put a bow on the podcast because design patterns are unique to God's creation, and AI is looking for patterns and trying to make sense of them. And so I bless your work, Joanna, in both AI and augmented cognitive assistance and also in your ministry and your writing. You're just an amazing person to me, so thanks for coming on the podcast today and I'll talk to you later.

Joanna Ng: Thank you. Thank you, Gretchen, my honor and pleasure to share my heart today.