Sometimes when I think about implementing Copiosis, I think about struggles people will face. Especially while trying to agree on algorithm variables. Competing reports, research and other data sources will put some into analysis paralysis Or worse, competing data factions might want to try to rig the process in their favor.
Take food for example. There are many competing ideas out there about what food, how much food and in what combinations best support humans. Whole advocacy groups now exist about veganism, vegetarianism, paleo, etc. for example.
Other groups exist believe what one eats matters less than how one feels or thinks about what they’re eating.
Ultimately the best measures show up in outcomes. Humanity has some idea about how food effects bodies. We can wait and watch. But do we need to?
Plenty evidence exist
Post-transition I don’t think we need to start such studies over from scratch. Many studies exist today showing how different diets effect different people. What matters more: preventing competing interests from trying to promote their studies over others.
Thankfully, the Net Benefit concept helps eliminate much of that competition. Net Benefit Rewards (NBR) aren’t money. So profit isn’t a thing in Copiosis. Getting rich is not about selling as many things as possible for as much money as the market allows. Getting rich means creating the most Net Benefit to people and planet. Since resources come at no cost that should be easy.
Enriching oneself using money creates many conflicts of interests. Often, producers will lie, or obfuscate information consumers need. They confuse or manipulate people into consuming harmful things. Or they’ll obstruct better products in favor of their own.
NBR: not zero-sum
In Copiosis the Net Benefit concept makes most of that go away. For one, since NBR gets awarded only after all factors are known, enriching oneself based on lies and deceit will prove challenging. Especially when Copiosis awards whistleblowers for uncovering lies and deceit!
Secondly, just because what someone offers is harmful, doesn’t mean they get no NBR when people consume it. For example, eating meat may or may not be good for people or the planet. Not how it’s currently produced. Nor in the way we prepare it, for example.
But meat offers many benefits to humans. Just because we produce it in not-so-good ways now, doesn’t mean we can’t do better. In the meantime, meat producers get NBR for feeding people.
So with NBR, it’s not a zero-sum game. A less-than-perfect product can still generate NBR.
Human value conflicts
Besides, NBR only allows access to luxuries, nothing more. Everything people need, they don’t need NBR to get. NBR conveys status and reputation as well. Status and reputation are not necessities however.
Still, the best way to get status and reputation happens through producing something maximally beneficial to people and planet and minimally harmful. Money represents no barrier. Nor can it corrupt anything as it often does today. So making beneficial things becomes easier. That means positive status and reputation happens easier too.
A population over focused on luxury accumulation could cause over focus on NBR accumulation. But I think we’ll struggle with something else.
Values from religion, culture, insecurity and fear will create the lion’s share of conflict. Especially as society works on decisions the algorithm needs. Thankfully, because of the algorithm’s recursive nature, the entire human population needn’t agree on everything.
Planet trumps people
Each region, nation, town, village, etc. can make their own decisions. Then reward NBR according to their local morals and values. So long as such decisions don’t impact other regions.
If they do, agreements “higher up” supersede local decisions. I would think for example, if people in one region agree to reward someone who pollutes a local major waterway, the lager, ecosystem level decisions will trump the local ones. Why? Because waterways play a global ecosystem function.
Locals still enjoy NBR accumulation from other activities though. I think that makes NBR and Copiosis really cool. People don’t depend on one income source, such as a job, to get what they need or what they want. Instead, they enjoy NBR income from a variety of sources (results from their actions) both large and small.
Artificial Intelligence works
Artificial intelligence will help too. I’m not suggesting AI will decide for us. Rather, it will help humans better understand their world. Each other too. It will also help humans sift through heaps of data.
Decision making processes and information will become more transparent and easily understandable through AI. And, AI will help people collaborate in decision making processes. Through AI people will see where other stand on issues important to them. Peer assemblies might play a role here.
It may not even require huge numbers of people coming together at certain times or places. AI may enable real-time decision making at the level of the individual, pinging people in real time. Then it might aggregate the real-time choices across cities, nations and regions. In this way diverse groups don’t need to know what other groups think or believe. That could eliminate a lot of potential conflict.
Thinking about what’s possible with computer-aided and AI-aided processes offers a lot of room for getting it wrong. I think challenges inherently exist in trying to predict beneficial future technologies. That’s because human ingenuity always represents a wild card. How we use future technologies often determines the future more than the technologies themselves.
The best science
Anyone following me knows I’m not a huge proponent of science. That said, science plays a significant role in Copiosis. Especially so in algorithm calculations. One problem with science is, it can be fudged. Especially when profit motivates people. Status can influence scientists the same way it does everyone else. They are human after all.
I advocate using “the best science” in calculating NBV. What does “the best science” mean? Of course, it means results from scientific processes done correctly with repeatable, consistent results. But it also means science free of biases, including profit-motive bias. Believe it or not examples of these kinds of processes exist.
Consumer Reports, for example, offers completely unbiased data on cars and trucks. This wikipedia article describes lengths through which Consumer Reports goes to preserve its independence.
Our algorithm is designed to make the best use of the best science, with the best science producing the best outcomes, as described here:
Food, healthy food and opinions
But bias-freedom gets harder when talking about some things. Let’s return to food, for example. Many studies out there purport certain things as healthy, when, actually, they may not be. Organizations and industries will (and have) cover up data or create misleading data to convince or bamboozle consumers into believing their output benefits them.
I love what Dr. Michael Herschel Greger says. He’s an American physician, author, and professional speaker on public health issues. He says what we know about food and nutrition already is good enough. The truth is out there, he’s basically saying, and it’s not rocket science. His organization offers bias free, non-profit science-based facts.
In other words, a lot of what we need to know, we know. I think that’s true on many, many subjects.
That said, I believe as we near Copiosis and people see how it strips away incentives for bias and manipulation, we’ll uncover a great human characteristic underlying our success so far: our desire to cooperate in trust of one another.
That will greatly amplify our reliance on the best science and boost what’s possible with Copiosis.