Can AI police itself? A futuristic story
18 minutes reading time, high school level. Or see the audio and video podcast links below.
Foreword
I wrote this as a story to make it easier to understand. This is about AI, which people have many warranted concerns about, such as concerns about privacy, job displacement, and the unknown. New technology is a difficult topic for people to understand. I understand that. Biblical references are included.
I worked in the field, and my primary job was to understand and explain. I use it multiple times a day. Even so, some of these ideas were new to me also, in this fast-moving field. Even the title, ‘Can AI Police Itself?’, is a gross oversimplification. But sometimes, a simplified story is the best way to start a complex conversation. Enjoy!
This story chapter is just the beginning. Next week, we’ll delve deeper into the impact of AI on the creative community. Then, we’ll explore the impact on jobs, influence on learning, artificial general intelligence and the differences between machines and people, and transhumanism—AI implants melding the brain with AI for total knowledge, and possible government and wealthy oversight.
Can we trust AI to regulate itself?
Also available as an audio podcast and video podcast. Podcast show links: Substack, YouTube video, Spotify, and Apple podcasts. These appear a day after blog-article posts.
The Truth Glitch in AI
Runklesty, the CEO of a technology company in 2028, was in the middle of a marriage crisis and looking for sound advice. For him, marriage was his world, but AI was an even bigger world that was affecting everyone’s world. It offered the entire knowledge of humanity at every person’s fingertip.
AI was world-changing, a force as transformative as any pivotal moment in human history, as big as religious figures had done, including turning the world upside down as Jesus had done, but not in the same way. How could he ever balance the two demands on his life? He had to save his marriage, but would he have to sacrifice one or the other? No! Unthinkable!
The deep plow of worry made cavernous grooves in his well-furrowed brow. Such was the nature of a CEOs job, always trying to stay one step ahead of competitors who worked in secret and always presented rude awakenings. Life and job were inextricably tangled.
Intuition told him a business crisis was looming, and his intuition was almost always right. He was waiting for the inevitable bomb to drop.
He called Amada. “Crap! Crap, crap, crap!” He stormed. “Don’t ask!” He hung up. Amanda was his only confidant in the business. She knew his moods well and wasn’t offended or even disturbed. Not that they were having anything close to an affair or anything intimate.
He could have said the same to his personal chatbot, which would have been less forgiving. The chatbot he chose was pragmatic, even rude, and it would have told him to, “Save the drama for your mama.” That was what he usually needed, the bare truth. He loved using AI for advice, but even something about AI was troubling him now.
Using AI was natural for him. His company had adopted AI for many things and used it extensively. They used it for software development of AI chat agents. He found it made very good decisions, so used it for management oversight of operations. Relieved of the mundane tasks of management, his managers were free to work on deeper problems so nothing important got by them because they were too busy to notice.
His company’s claim to fame was innovation, and it made them a favorite with both business and consumers. AI was his life.
His nagging doubts started with his wife. It was a tipping point that triggered this wellspring of doubts. She said something about seeing a marriage counselor. He thought everything in their marriage was fine and replied jokingly, “Sometimes I don’t know about you.”
She retorted, “I never know about you.”
He laughed, thinking it was a joke, but she continued, “You’re not married to me. You’re married to your job. I want a real marriage where you actually show up!” But a marriage counselor? Runklesty thought to himself in alarm.
Yes, he knew this was a common complaint among CEOs and other people with heavy job responsibilities that meant the company would die without them on task seemingly sixteen hours a day. When weekends arrived, if he hadn’t brought important work home, he was too tired to do anything fun. Some CEOs even got accused of having affairs. But this wasn’t him. He loved his wife and would never cheat, not even emotionally.
He looked at himself in the executive bathroom mirror. Maybe it’s the growing bald spot on my head. He tried to pull the tuft of hair at the front backward to cover the round spot in the middle. Maybe it’s my belly paunch. He lifted it thinking maybe exercise might tighten the muscles and lift it. But when would he have time for exercise. At fifty-two, what could people expect?
Then it struck him. Was she bothered by the same problems in herself? Was she feeling unloved and unlovable because of her aging physical appearance? Am I an uncaring, selfish boor for not noticing? Maybe they did need counseling. Or maybe I just need to be a better person. We’ll talk.
When he got to the office that day a week ago, he consulted an AI chatbot that was a specialist on marriage. The chatbot told him, “You’re a man, leader, potentate in the marriage, so put your foot down.”
Taken aback, he tried a different chatbot and was given very different advice. “Be there for her, and to make it a point to do it regularly and as she needs.”
Well, he had kind of depended on her network of female friends to fill that role. Maybe I’m wrong. Anyway, he couldn’t escape the thought that there was something wrong with AI chatbots to give him such conflicting advice.
Every once in a while, Runklesty noticed a flaw in AI. But these were obvious and easily avoided. They didn’t rankle Runklesty. He had developed great trust in AI. AI made fewer mistakes than his employees, and he certainly didn’t fire them for mistakes. They felt bad, so he simply asked them if they had learned anything, and what would they do different next time.
Then Runklesty started noticing subtle things that other people in his organization seemed to miss. There seemed to be a lack of … he couldn’t put his finger on it … but it was like watching the same movie over and over. And certain things seemed to include an element of bias. Why are my AI guardian agents not catching this? Why are my programmers not noticing this? Could these problems be addressed through a task force?
Am I innovative enough in our relationship just as I am in business. He was plagued with all these thoughts when his cell phone interrupted his deliberations about his wife and his dilemma about chatbot differences.
He stepped out of the bathroom to avoid the room echo, and automatically answered it. Few people had his direct number. If it rang it was important. He had mercilessly scolded some sales people who had somehow gotten his number. It was unforgivable.
“Runklesty, I just wanted to give you a heads up. We’ve been given a better offer on a better product.”
Runklesty thought he knew what was coming. Price negotiation. As a well-trained negotiator, he would stand firm and give very little, while extolling the virtues of his product over competitors, and the money saving and money producing benefits it had for his customer. It always worked.
“I’m listening. How is their product better? Price?”
“No, sorry, if it was just price we would stick with your chatbot. This new one offers a level of creativity we haven’t seen anywhere before. It augments our people by helping them identify unexpected trends in the market, related customer feedback across the Internet, evaluates the results, helps them evaluate the new market conditions with a weighted average, and then makes recommendations. It taps into quantum computers so it has answers within just a few minutes. Do you have anything like that in the pipeline?”
“We’re thinking in that direction if you can wait a few months,” Runklesty offered. He thought quantum computers in actual use wouldn’t occur until 2030, except for computers that simulated quantum computers with algorithms. They hadn’t thought in that direction at all, but they were now.
“Well, I can hold off for three months. Let me know what you get.”
The conversation over, Runklesty was jolted from personal problems to business problems. Three months was a very short development cycle for software, even with the great team he had. The inevitable had landed with brute force.
He called the chatbot developer, product manager, and marketing manager into his office. The developer, Nicholas, and marketing manager, Emily, sat before him while the product manager, Sarah, stood. Emily had back problems and preferred an ergonomic seat or to stand and lean on a wall. She cut a striking figure he wasn’t supposed to notice, with her jet black hair, flashing eyes, abundant energy, and bulldog approach to marketing.
In contrast, Sarah, the product manager, was confident, relaxed, the picture of quiet strength. Nicholas, the developer, had the same quiet confidence and usually spoke authoritatively about all aspects of software development. Nicholas liked Sarah, but she didn’t know he existed, he thought, but she also had an eye for him. She just wouldn’t reveal it.
“This is a private discussion,” Runklesty began. They all nodded affirmative. “I just got a call from a customer who said they were offered a chatbot that uses a large language model (LLM) that is connected to a quantum computer. It specializes in new market analysis and gets them thorough answers within a few minutes. How long would it take us to develop something like that?”
The three looked at each other as if Runklesty was speaking an unknown language. Then they began to calculate in their heads.
Nicholas the developer spoke first. “If we knew where to start, and it was just me working on it, and not having to load in all the data, we might be talking about a year.”
“There you go,” said Emily the marketing manager. Sarah, the product manager nodded in unison.
“What if we needed to have a demo going in three months?”
Nicholas immediately shook his head no. “You know what? I couldn’t push a team that hard. They would be sleeping here and working seven days a week, sixteen hours a day. We would burn them out and lose them.”
“What if we brought in some experts. A few years ago the Chinese developed a ChatGPT equivalent in two months. Could we do that?”
“Harnessing an LLM to a quantum computer? That’s new ground. I mean- “Nicholas shrugged and shook his head.
Emily said, “Quantum computers are really expensive. I mean, we could buy a couple, but hooking up to cloud computers would probably be better.”
“Developing software tools and programming languages for our specific application, enabling us to write quantum algorithms would be a lengthy process.” Nicholas said. “I would need help. We could outsource a consultant and try it.”
Runklesty looked around him at the team. This was foreign ground and they were noncommittal. “Nicholas, you would understand all this better than the rest of us. Put some feelers out and see if you can get a consultant in here. They started making quantum chips in 2024. Surely there is some off the shelf languages we could use, and automated data chunking to speed up the process.”
“I know some people in my online groups.”
Emily said, “Make sure it’s semantic search, not specific word search. I hate having to search multiple times because I don’t use the exact word.”
Sarah said, “Let’s keep this restricted to a demo. If it fails in customer use, it will be a major setback for sales.”
The more Runklesty thought about the company’s current lapse of innovation, the more fearful he became. They were making incremental gains, but he knew well what happens to companies that don’t innovate. Competition gets ahead of you. They either go out of business or buy other companies’ technology to survive. Cannibalism of the market.
The differences in chatbots really bugged him. It wasn’t a good time to stress over little things, but little things can grow into mountains. He needed answers.
He called his developers, product managers, and marketing managers into a meeting. He saw the worried faces of people who knew a meeting called on short notice was ominous. Something huge must be happening. Layoffs?
The lavishly appointed conference room with its real leather chairs with full motion and rocking, also used as a board room, didn’t shout layoffs. It shouted success. And the company financials were fine. What then could it be? Rumors were buzzing by the water cooler as they always did. Speculation ran wild.
The assembled group looked out of place in blue jeans instead of business suits sitting in the leather chairs opposite the wood grain paneling. But software development is a blue jeans environment. Show up in a suit and you’re asking to be fired.
Seeing the anxious looks on people’s faces, Runklesty gave them a huge, disarming smile. “I’ve noticed something that is really beginning to bother me,” he began. “And you can all breathe a sigh of relief. It isn’t any of you.” The room sighed and visibly relaxed. People began rocking in their chairs, but sat forward again attentively when Runklesty began to talk.
“We’re an entrepreneurial company. We innovate. We bring exciting new things to market. You all know our AI chatbots are market leaders, and we’re doing a good job of staying ahead of the competition. But the smell of death is here. I look around and all I see is repeat performances and incremental gains. To keep the market excited, you have to do exciting things.”
He sighed. “We’re as dead as the church I go to. There’s not a sign of anything alive in it. It’s the same thing over and over again. I’m always soothed to sleep, never challenged.” This evoked a few groans and a few laughs.
“Not that I need challenged. I have enough challenges here.”
Sarah said, “Jesus’ message doesn’t vary. It’s eternal.”
“Sometimes bright, colorful packaging helps,” Emily said. The room buzzed.
When the room quieted, the people looked surprised and puzzled. Something new and exciting was needed.
Emily had looked at the market and seen ways they could improve their product to stay ahead of the competition. Am I not doing my job well enough? she asked herself.
Sarah said, “Church is supposed to bring comfort and inspire us to look to God. I need that.”
“We all do, But here’s the problem,” Runklesty said. “New packaging is incremental. No, actually, it’s just a lateral move. Going sideways isn’t moving forward. We know that in business, but even churches could learn from that.
“I mean, we have to keep up with the times. For a while many churches thrived on End Times theology. The end of the world thing has burned out and doesn’t get attention anymore because it gained us nothing except morbid curiosity.
“People are interested in the here and now, not pie in the sky mythology that isn’t any help with their problems. So, churches can look at their message and see how it applies in new ways to new things. Not incrementally, but in exciting steps that keep people engaged and excited to be part of it. Do you get what I mean? Things that offer spiritual meaning and purpose, not quaint sayings.”
“Quaint sayings!” Sarah said, aghast.
“Look, we’re off topic.”
“Please explain!” Sarah demanded.
“Okay, Jesus talked about investing. Interest on loans was not allowed in Judaism, but times had changed and it was customary in the land. So Jesus used it. Jesus addressed many things that weren’t in the teachings of Judaism, such as immortality, Heaven, and Hell. For Jews it was ashes to ashes, dust to dust. The times had changed and he addressed these.
“The Apostle Paul talked about running the race. The Romans and Greeks were sportsmen and racing was common. It wasn’t common for Jews. The Apostle Paul was in the territory of the Romans and ministered to non-Jews. It was the times, so it made a good metaphor and encouraged followers to work harder for Jesus.
“If we look at the changing needs of people today, the changing times, the changing climate of needs, we can use these both literally and figuratively to speak to them and help them. Understand? I think it’s a good metaphor for business.”
Emily looked up from her pad of paper. She was a prolific note taker. “It’s a little preachy, but I get it.” Sarah finally nodded acceptance.
“I know, you Millennials are more spiritual than religious. I mean, why go to a dead church?”
They all laughed.
“Anyway, I want a team to look at AI chatbots and find out why there are major differences between them. And I want another team to look at why AI is not telling us innovative things. You guys form your teams and go to it. Highest priority.”
The people in the room immediately started talking to one another. As they drifted out of the room, teams began to form with three or so members that worked well together. They were on it. He knew he could count on them.
Runklesty immediately visited one of his very trusted product managers who he had sometimes talked to about personal issues and found they were discreet.
“Amanda, I would like for you to dig into something personally and be discreet. It’s personal.” He had known Amamda for nearly twenty years. She was a mother of three lovely children he had met at company picnics. He knew she had self-image issues, so he liked to boost her confidence with confidant trust. She was really great at her job so she deserved the confidence.
“Of course,” she replied. “Anything.”
He explained to her the dilemma he had with chatbots who gave him conflicting information about marriage.
“That’s unhealthy,” she replied, gratified he had ignored the first chatbot. “Please give me the name of the chatbots and I’ll look into it.”
“And, please include this in our group discussions without giving any of my personal details. I think it’s something important for us all to know.”
She smiled and nodded.
The next afternoon the group convened again, having done a mountain of research, much of which was aided by AI, which had a much broader view of the subject from authoritative sources and could do the research in mere seconds.
Amanda gave Runklesty a smile. He knew she had informative news, so he called on her first.
Sarah began, “I researched chatbots to understand how some could have such different information.” She knew she didn’t have anything really new to offer, but continued.
As you all know, our chatbots use commercial sources like Google Gemini and ChatGPT. They can then be tailored to include information only available in a company. They solved the problems with AI hallucinations and model drift.
This part might be new to some, she thought. “This part might be new to some. As many also know, chatbots can be created to use only certain information. This creates a problem in that the information may not be authoritative. For example, white supremacists could create a chatbot using only their collection from decades of very biased information and then advertise it as some kind of self-help chatbot online on some website people don’t suspect is theirs.”
The group groaned. “What about guardian agents? Emily asked. “I mean, they’ve been around since 2024. I have one in my web browser that’s supposed to catch crazy and unsafe stuff on all web pages and AI outputs. Aren’t they supposed to detect bias and warn the user?”
“Not all browsers and chatbots use guardian agents,” Nicholas said.
“Mine doesn’t,” Runklesty said. “My web browser is on an experimental AI computer and doesn’t offer them.”
Amanda nodded at him and continued, “It’s up to the developer and owner. If a guardian agent would contradict or provide a different point of view, such as on religious opinion, it might not be used. It could freely put women in a lower status, demean other religious beliefs, support child pornography, even support Satan worship. It could be subtle, and users wouldn’t even know it.”
Runklesty shook his head. “A verse in Proverbs says, ‘There are six things the Lord hates—no, seven: haughtiness, lying, murdering, plotting evil, eagerness to do wrong, a false witness, sowing discord among brothers.” (Proverbs 6:16-19 (NRSV))
Emily laughed. “That’s your opinion. Not that I disagree. But some people might see lying as healthy for business and other relationships. It could even get them out of trouble with the law when they were unexpectedly at the scene of a crime they didn’t commit.”
“Would we expect any less than lies from marketing?” Sarah asked with a smile, and they all laughed.
Runklesty nodded. “Yes, it’s true, we are talking about the area of opinions. We have to ask ourselves who is to judge.”
Nicholas said, “We can’t expect AI to decide if opinions are true. That’s a philosophical and ethical challenge. Truth comes from many perspectives.”
“Doesn’t that place us at a moral crossroads?” Emily asked. “In a moral dilemma?”
“And doesn’t it make the playing field flat for all kinds of information?” Sarah asked.
“And an even larger question, can we relegate judgment to AI and abandon our own role? As a developer, I wouldn’t know how to make AI the judge of information truth.”
“I’m Hindu. Even the Bible you refer to isn’t completely clear on truth and ethics. Didn’t the Apostle Paul say, ‘All things are permitted for me, but not all things are beneficial. All things are permitted for me, but I will not be dominated by anything.’ I hear this verse from Christians all the time, but what does that even mean? Not dominated? Or another translation, not all things are helpful. Does it mean Christians can commit murder once, but not be dominated into doing it again?”
The faces around the table were blank. Suddenly Sharon said, “The Apostle Paul said, quoting Jesus, ‘Owe no one anything, except to love one another, for the one who loves another has fulfilled the law. Love does no wrong to a neighbor; therefore, love is the fulfilling of the law.’” (Romans 13:8-10)
“Sweet,” Nicholas said. “I don’t know anything about Bible verses. I can tell you about LLMs. At this point they know everything there is to know and the Supreme Court gave them access to everything because not doing so is a clear and present danger to society. Those who feed them data to train them are selective about using authoritative sources. Well, most of them are.
“But then all kinds of data might be fed it from scanning the Internet. Customer feedback is used to tell it what is incorrect or immoral. Feedback creates a down-rating that demotes data in significance so that it doesn’t appear in results unless specifically requested. That takes care of things like White Supremacy which the public is mostly against.”
“You would think I would know that,” Runklesty said. “But I didn’t.”
“So what you’re saying is that if it goes against the majority public opinion, AI is forced to reject it?” Emily asked.
Nicholas nodded in the affirmative.
“Then how are we to grow as a society?” Emily mused. “Do the wealthy create downgrades if something opposes capitalism? Are we stuck in place just as we are?”
“Who is to decide what is authoritative?” asked Nicholas.
“Public feedback,” shouted three of the people at the table.
Nicholas continued, “The people who train LLM models look for authoritative information from scholarly papers. AI struggles with understanding context, nuance, and the difference between facts, opinions, and satire in unstructured data. In fact, this can actually lead to censorship.”
“That explains a lot,” Sarah replied. No one laughed. This was significant. “You know, on social media I get flagged a lot for posts that AI thinks are similar to other posts that have been exorcised. And they aren’t. It’s different context.”
“I have an even bigger concern,” Nicholas added. “AI bases its knowledge of the collection of human knowledge. But human knowledge changes over time as science and other knowledge increases. Doesn’t that create a feedback loop of opinion. AI tells me so, so I tell the world so, and AI sees that opinion reinforced and tells it to us again. It’s an echo chamber.”
Emily said, “LLMs are supposed to always be in search of new information. That would keep them updated and stop the echo chamber.”
“Part of what they would see is new is what they’ve told people and they have put it on the Internet.” Nicholas countered her. “It’s a reinforcement loop even if its looking for new information.”
Emily shot back, “I think the programmers and people who feed it information would account for that. It can weight information. It can label things as new opinions and maybe unreliable.”
Runklesty smiled, shook his head, shrugged, then said, “I started this by quoting the Bible. Obviously, I’m in over my head in this group in both Bible and technology. I think we’ve raised more questions than answers.”
Some looked smug, some embarrassed. Some felt it wasn’t good to show up the “boss,” even if he was very inclusive.
“Great work, all of you. Very revealing and very thought-provoking information. So let’s work on some of these other questions and come back tomorrow before the staff meeting.”
Sarah shouted, “I have a band. I’m really worried about AI taking over music!”
A marketing person said, “Tell me about it. I’m a fiction writer in my limitless spare time.” Everyone laughed. “I make fifty cents a week on novels. I want to know if AI will replace me. It’s already writing most of our marketing material.”
“I used to be a math teacher,” one of the programmers said. “AI writes most of my code, and is a better architect than me. Not better than Nicholas, though. I’m worried my skills are going out the window, and AI is going to kill our ability to think critically and creatively. I wonder what I’m doing working for an AI company. Well, at least I have a job.”
The group let out a collective groan and disbanded with a feeling of doom. Would the answers be as confusing and horrifying as the chatbot information they uncovered?
Runklesty, his head rumbling from all the new problems of the day, went home to save his marriage.
His wife, Sharon, was lounging in their bedroom quarters with a popular alcoholic drink and watching a movie. She paused the movie and looked up at him.
His thoughts about his appearance on his mind, he said, “Darling, do you want to get a face lift? We can afford it, you know.”
She looked at him with horror. “Do you think I need one? Is that why you don’t look at me anymore? Is that why you hide in your office and not spend time with me?”
“No!” he said, alarmed, realizing he had said the exact wrong thing and made the situation worse. What is wrong with me? “I’m having doubts about my own appearance and wondered if you’re wanting a divorce? I thought maybe you might be having the same doubts.”
He saw a tear in her eye. She rushed to him and hugged him. “I love you. I don’t want a divorce. I want you.”
He gave her a huge hug back. They stayed in a tight embrace for a long moment. Then he whispered to her as they remained embraced. “I want you, too. I don’t know what this is about exactly, but we will talk it out and fix it. I promise.”
For the first time that day Runklesty relaxed. He thought, Somehow everything is going to be alright. I just have to work at it.
Story to be continued covering the creativity community, then impact on jobs influence on learning, artificial general intelligence and differences between machine and people, and transhumanism (AI implants for total knowledge with government and wealth oversight of thoughts and actions).
Reference verses
“For there are six things the Lord hates—no, seven: haughtiness, lying, murdering, plotting evil, eagerness to do wrong, a false witness, sowing discord among brothers.”
– Proverbs 6:16-19 (NRSV)
“You aren’t made unholy by eating nonkosher food! It is what you say and think that makes you unclean.” – Matthew 15:11 (TLB)
“All things are permitted for me,” but not all things are beneficial. “All things are permitted for me,” but I will not be dominated by anything.” – 1 Corinthians 6:12
Conclusion
AI has significant challenges to overcome, and it will take years. Some of these challenges will be up to the public to engage in.
Providing feedback to AI so that it gets a better sense of what is reliable information is very important. Labeling information so that AI knows if it is opinion or fact is also important for news and other organizations.
Selecting reliable sources is also important. Otherwise chatbots will become indoctrinations into ways of thinking that their makers want you to believe. Knowing which ones are reliable will likely be a public effort. Generation Z is better at this than previous generations.
AI also has to learn how to break out of echo chambers when information it puts out is fed back into it through online writers. Diversity of information is important or society that depends on AI will get stuck.
AI can police itself to some extent through guardian agents that are now in development. Current ones guard against harmful websites. Others will identify websites that are known for bias and misinformation. Others will read information in your browsers and alert you when it’s malicious or not authoritative. But everyone needs to engage their critical thinking skills to suspect when a website or chatbot is malicious or misinforming them.
Some things you might want to become more familiar with by looking them up using Google Gemini, ChatGPT, or Claude, or follow the links:
- AI agents
- Chatbots
- Quantum computers
- Large Language Models (LLMs)
- AI hallucinations and model drift
- AI and exposing private information
- Why AI models might seem to perform worse over time
- AI Doomers Versus AI Accelerationists Locked In Battle For Future Of Humanity
“Outrage (righteous wrath) can be good if it compels us to positive action but not to hate.” – Dorian Scott Cole
“With hate, we have more to lose than gain – break the cycle” – Dorian Scott Cole
Probability Space
What probability spaces can we open in our minds to stay up to date on the benefits and dangers of AI?
(A probability space is where all of the elements necessary for something to happen are present and it’s almost inevitable. All it takes is intention.)
Potential Space
If you think creatively and allow your mind to wander and explore, what does the future hold for improving human abilities with AI? Interpret this widely, not narrowly.
(A potential space is a virtual space in our minds where entirely new things can take shape.) More: Is Music A Form Of Prayer?
Would love to hear your thoughts in the comments below. This helps me improve my work.
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Below is information for church planning to minister to new generations, building a community of action, service opportunities, Education Opportunities for new generations, and descriptions of the author’s books.
Church planning season – strong impact course
How can churches minister to new generations if they won’t come to church? The church has been losing people at 1% a year, and now most of new generations won’t come.
I developed and presented a course on understanding and working with new generations. I would like to say I had rave reviews, but on a scale of 1 to 5 it averaged 4.5. Well, some people were raving.
The course helps people understand new generations, their values, and their differences. It helps people understand how to build a bridge to them and minister to them. The old worn-out things we used to do don’t work, and for good reason. This solutions-focused course enables people to find new ways, appropriate ways, to minister to these generations in their local circumstances. It’s for church groups and generates deep discussion. </p>
Free video preview of the course
Course on Udemy: <a href=”https://www.udemy.com/course/understanding-and-working-with-new-generations/learn/lecture/46266901#overview”>Understanding and Working with New Generations</a>
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– Dorian
Our answer is God. God’s answer is us. Together we make the world better.
Restore and recreate. Take time to celebrate life. Laugh, sing, and dance regularly, even every day. Happy. This is why we dance to celebrate life: Reindeer actually running and dancing.
Building a Community of Action
New Way Forward community
Can we make positive change in our world and end a lot of suffering?
Helen Keller, who was both blind and deaf, said: “Although the world is full of suffering, it’s also full of the overcoming of it.”
The human spirit yearns for a world without suffering, but it’s through facing challenges that we progress. The world isn’t perfect, but together we can create a future with less hardship. Famine, discrimination, gun violence, and injurious economic and educational disparities are complex problems, yet understanding their root causes empowers us to find solutions.
Launching in first quarter 2025, the New Way Forward community will connect individuals seeking practical solutions and creating lasting change. We’ll focus on understanding problems and their solutions, and how to effectively create change.
Join us in building a brighter tomorrow! New Way Forward on Facebook.
Civic service opportunities
Do Unto Others Kindness Campaign, and civic engagement.
United Methodist Church Volunteer Opportunities.
Join or support Zero Hour and amplify the voices of youth organizing for climate action.
Peoples Hub. Resistance, Resilience, Restoration, Re-imagination. Online Popular Education. For movement workers to learn, connect, collaborate, and strategize – in and across the disability justice and solidarity economy movements.
Stakeholder Capitalism – a video podcast series from the World Economic Forum. Can capitalism be made to work for all of us – and to improve rather than destroy the state of the planet?
General service and aid opportunities (on One Spirit Resources Website). To add your service opportunity to the One Spirit Resources list, contact the author (me) through Facebook Messenger. Note that I only friend people I know.
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Education Opportunities for new generations
Becoming an Entrepreneur – MITx online
Evaluating Social Programs – MITx online
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Bible scripture verses are New American Standard Version (NASB), unless noted.
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Author and books
Appease the Volcano: What does God require from people? The voices of the ancients from many religions echo much of the same things: It starts with law, then mercy and forgiveness, then love. Love is a major emphasis in all major religions and replaces law.
The Prophetic Pattern: Ancient and Modern Prophecy: How to distinguish the intent of various types of prophecies and oracles, both ancient and modern.
Preparing For the Future Of Work and Education: Analysis of the kinds of jobs that AI and Robotics will displace, and the educational requirements for them. AI will replace or augment thirty percent of jobs. This is an in-depth analysis citing many authoritative sources.
Author Website: Dorian Scott Cole
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