Misinformation is false or inaccurate information - getting the facts wrong. Provided the data collection process is engineered with proper intent, a statement like ‘data doesn’t lie’ is misinformation. If the entire data collection process is designed deliberately to mislead - intentionally misstating the facts, that’s disinformation. Our modern world is full of both - let’s dive in.

The spread of misinformation and disinformation has affected our ability to improve public health, properly address climate change, or perhaps even maintain a democracy. Now it’s creeping into our homes, schools, and workplace conversations.

So how and why does misinformation spread?

The behavioral models behind it prove that exposure to misinformation increases the odds that people will believe it. Couple that with our instant, social, feed-induced communication platforms and you have a recipe for a mess. Peer-to-peer sharing can create echo chambers that bind and isolate online communities with similar views. This unique feature of social media encourages viral content with low oversight. In essence, it’s a polarized breeding ground for BS.

Similar to market-niche branding, misinformation travels fast in properly targeted groups. These groups are especially susceptible to misinformation attacks. Hot-button topics tend to top the charts with clicks, likes, and pageviews - a marketer’s dream. If you’re looking for more on this, here’s a good article from the American Psychological Association that illustrates the psychological factors that make people susceptible to believing and acting on misinformation.

Nobody mentioned politics - so if you’re thinking it’s a Right or Left thing it would be very beneficial to check your bias at the door.

It’s true. I read it online.

The network effect is incredibly powerful when discussing mis and disinformation. Routed in business and economics, the network effect illustrates the idea that when more people use a product, service, or platform its value increases. When the network reaches critical mass, a bandwagon effect can result. As the network continues to become more valuable with each new adopter, more people are incentivized to adopt, resulting in a positive feedback loop. Multiple equilibria (more than one solution) and a market monopoly are two key potential outcomes in markets that exhibit network effects. Consumer expectations are key in determining which outcomes will result. If the network result is pre-programmed or pre-determined, the misinformation converts to disinformation, resulting in a feedback loop - good or bad.

But there’s hope

One of the leading emerging technologies in decentralized blockchain is called Zero-Knowledge Proof or Protocol. In cryptography, a ZKP is a method by which one party can prove to another party that a given statement is true while avoiding conveying to the verifier any information beyond the mere fact of the statement’s truth. It’s a BS meter that doesn’t feel the need to call anyone out. Using our example above, it would look something like this:

With the deluge of information that has been added online, we’re left guessing what’s fact and what’s not. Heck, we’re even questioning the very definition of fact - or the science behind what supports it. Luckily, as we continue down the path toward globalism, widely accepted views allow for consensus. These mechanisms are deeply involved in proofing.

Taking a step deeper for the researchers of the bunch:

• Blockchain Oracles

• ZKP for Decision Tree Predictions and Accuracy

• ZKML

• zkSNARK

As disinformation campaigns increase and misinformation continues to spread, we will become increasingly dependent upon agent-assisted proofing. The deep fakes will get deeper and the choreographed attacks will become more sophisticated. Nature runs on instinct and human beings have consciousness and awareness. While the machines will eventually become better at detecting and preventing the BS, it’s up to us keep an open mind about the origin and provenance of fact.

Misinformation is false or inaccurate information - getting the facts wrong. Provided the data collection process is engineered with proper intent, a statement like ‘data doesn’t lie’ is misinformation. If the entire data collection process is designed deliberately to mislead - intentionally misstating the facts, that’s disinformation. Our modern world is full of both - let’s dive in.

The spread of misinformation and disinformation has affected our ability to improve public health, properly address climate change, or perhaps even maintain a democracy. Now it’s creeping into our homes, schools, and workplace conversations.

So how and why does misinformation spread?

The behavioral models behind it prove that exposure to misinformation increases the odds that people will believe it. Couple that with our instant, social, feed-induced communication platforms and you have a recipe for a mess. Peer-to-peer sharing can create echo chambers that bind and isolate online communities with similar views. This unique feature of social media encourages viral content with low oversight. In essence, it’s a polarized breeding ground for BS.

Similar to market-niche branding, misinformation travels fast in properly targeted groups. These groups are especially susceptible to misinformation attacks. Hot-button topics tend to top the charts with clicks, likes, and pageviews - a marketer’s dream. If you’re looking for more on this, here’s a good article from the American Psychological Association that illustrates the psychological factors that make people susceptible to believing and acting on misinformation.

Nobody mentioned politics - so if you’re thinking it’s a Right or Left thing it would be very beneficial to check your bias at the door.

It’s true. I read it online.

The network effect is incredibly powerful when discussing mis and disinformation. Routed in business and economics, the network effect illustrates the idea that when more people use a product, service, or platform its value increases. When the network reaches critical mass, a bandwagon effect can result. As the network continues to become more valuable with each new adopter, more people are incentivized to adopt, resulting in a positive feedback loop. Multiple equilibria (more than one solution) and a market monopoly are two key potential outcomes in markets that exhibit network effects. Consumer expectations are key in determining which outcomes will result. If the network result is pre-programmed or pre-determined, the misinformation converts to disinformation, resulting in a feedback loop - good or bad.

But there’s hope

One of the leading emerging technologies in decentralized blockchain is called Zero-Knowledge Proof or Protocol. In cryptography, a ZKP is a method by which one party can prove to another party that a given statement is true while avoiding conveying to the verifier any information beyond the mere fact of the statement’s truth. It’s a BS meter that doesn’t feel the need to call anyone out. Using our example above, it would look something like this:

With the deluge of information that has been added online, we’re left guessing what’s fact and what’s not. Heck, we’re even questioning the very definition of fact - or the science behind what supports it. Luckily, as we continue down the path toward globalism, widely accepted views allow for consensus. These mechanisms are deeply involved in proofing.

Taking a step deeper for the researchers of the bunch:

• Blockchain Oracles

• ZKP for Decision Tree Predictions and Accuracy

• ZKML

• zkSNARK

As disinformation campaigns increase and misinformation continues to spread, we will become increasingly dependent upon agent-assisted proofing. The deep fakes will get deeper and the choreographed attacks will become more sophisticated. Nature runs on instinct and human beings have consciousness and awareness. While the machines will eventually become better at detecting and preventing the BS, it’s up to us keep an open mind about the origin and provenance of fact.