Donald Trump can change the temperature of a room with a sentence. One minute he is certain, the next he is backtracking. One day he is threatening, the next heDonald Trump can change the temperature of a room with a sentence. One minute he is certain, the next he is backtracking. One day he is threatening, the next he

Trying to predict what Trump will do next is bad for your brain — according to science

5 min read

Donald Trump can change the temperature of a room with a sentence. One minute he is certain, the next he is backtracking. One day he is threatening, the next he is hinting at a deal. Even before anything concrete happens, people brace for his next turn.

That reaction is not just political. It is what unpredictability does to any system that requires stability. To act at all, you need some working sense of what is happening and what is likely to happen next.

One influential framework in brain science called predictive processing suggests the mind does not wait passively for events. It constantly guesses what will happen, checks those guesses against reality, and adjusts.

A brain that predicts can prepare, even when what it prepares for is uncertainty.The gap between what you expect and what actually happens is known as a prediction error. These gaps are not mistakes but the basis of learning. When they resolve, the brain updates its picture of the world and moves on.

This is not about what anyone intends, but about what unpredictability does to systems that need some stability to work. Trouble starts when mismatches do not resolve because the source keeps changing. People are told one thing, then the opposite, then told the evidence was never real.

The brain may struggle to settle on what to trust, so uncertainty stays high. In this view, attention is how the brain weighs up what counts as best evidence, and turns the volume up on some signals and down on others.

Uncertainty can be worse than bad news

When this keeps happening, it’s hard to get closure. Effort is spent checking and second guessing. That is one reason why uncertainty can feel worse than bad news. Bad news closes the question, uncertainty keeps it open. When expectations will not stabilise, the body stays on standby, prepared for many possible futures at once.

One idea from this theory is that there are two broad ways to deal with persistent mismatch. One is to change your expectations by getting better information and revising your view. The other is to change the situation so that outcomes become more predictable. You either update the model, or you act to make the world easier to deal with.

On the world stage, flattery can be a crude version of the second route, an attempt to make a volatile person briefly easier to predict. Everyday life shows the same pattern, such as unpredictable workplaces. When priorities change without warning, people cannot anticipate what is required. Extra effort may go into reducing uncertainty rather than doing the job.

Research links this kind of unpredictability to higher daily stress and poorer wellbeing.

The same pattern shows up in close relationships. When someone is unpredictable, people scan tone and try to guess whether today brings warmth or conflict. It can look obsessive, but it is often an attempt to avoid the wrong move.

Studies link unpredictable early environments to poorer emotional control and more strained relationships later in life.

The strain does not stay in thought alone. The brain does a lot more than thinking. A big part of its work is regulating the body, such as the heart rate, energy use and the meaning of bodily sensations.

It does this by anticipating what the body will need next. When those anticipations cannot settle, regulation becomes costly.

Words matter here in a literal sense. Language does not just convey information. It shapes expectations, which changes how the body feels.

Trump can do this at a distance. A few words about a situation can raise or lower the stakes for people, whether in Minneapolis or Iran. The point is that signals from powerful, volatile sources force others to revise their models and prepare their bodies for what might come next.

Communication is a form of regulation. Clarity and consistency help other people settle. Volatility and contradiction keep them on edge.

When a single voice can repeatedly unsettle expectations across millions of people, unpredictability stops being a personal stress and becomes a collective regulatory problem.

How to deal with unpredictability

So what helps when unpredictability keeps pulling your attention? Try checking for new information if it changes your next step or plan, otherwise it just keeps the uncertainty alive.

When a source keeps changing, reduce the effort spent trying to decode it. Switch to action. Set a rule that makes the next step predictable. For example, read the news at 8am, then stop and get on with your day.

Learn where not to look. When messages keep reversing, the problem is not a lack of information, it is an unreliable source.

Biological systems survive by limiting wasted predictions. Sometimes that means changing your expectations; sometimes it means changing the situation. And sometimes it means accepting that when Donald Trump is talking, the safest move is to stop trying to predict what comes next.The Conversation

Robin Bailey, Assistant Professor in Clinical Psychology, University of Cambridge

This article is republished from The Conversation under a Creative Commons license. Read the original article.

  • george conway
  • noam chomsky
  • civil war
  • Kayleigh mcenany
  • Melania trump
  • drudge report
  • paul krugman
  • Lindsey graham
  • Lincoln project
  • al franken bill maher
  • People of praise
  • Ivanka trump
  • eric trump
Disclaimer: The articles reposted on this site are sourced from public platforms and are provided for informational purposes only. They do not necessarily reflect the views of MEXC. All rights remain with the original authors. If you believe any content infringes on third-party rights, please contact service@support.mexc.com for removal. MEXC makes no guarantees regarding the accuracy, completeness, or timeliness of the content and is not responsible for any actions taken based on the information provided. The content does not constitute financial, legal, or other professional advice, nor should it be considered a recommendation or endorsement by MEXC.

You May Also Like

Top NYC Book Publishing Companies

Top NYC Book Publishing Companies

New York City has been the epicenter of American publishing for generations, but “NYC publishing” isn’t just one lane. Today’s landscape includes two very different
Share
Techbullion2026/02/06 14:02
Sensorion Announces its Participation in the Association for Research in Otolaryngology ARO 49th Annual Midwinter Meeting

Sensorion Announces its Participation in the Association for Research in Otolaryngology ARO 49th Annual Midwinter Meeting

MONTPELLIER, France–(BUSINESS WIRE)–Regulatory News: Sensorion (FR0012596468 – ALSEN) a pioneering clinical-stage biotechnology company which specializes in the
Share
AI Journal2026/02/06 14:45
AI Crypto Trading Secrets: What They Won’t Tell You About Profits and Pitfalls|9-Figure Media

AI Crypto Trading Secrets: What They Won’t Tell You About Profits and Pitfalls|9-Figure Media

AI crypto trading is everywhere, and every YouTube guru claims their bot mints money while they sleep. Sounds dreamy, right? However, most don’t discuss the full story, the wild profits possible, and the lurking pitfalls. As someone obsessed with the intersection of artificial intelligence and digital assets, let me pull back the curtain on the realities of algorithmic trading in the crypto jungle. Here’s what nobody tells you: 87% of retail traders using automated systems lose money within their first year. The marketing materials show cherry-picked results. The testimonials come from paid affiliates. But here’s the twist. The remaining 13% who succeed aren’t just lucky. They understand something the majority misses entirely. The Reality Behind the Hype The crypto world loves success stories. You’ve probably seen them. “I made $50,000 in three months using this bot.” What they don’t mention? The $200,000 they lost by testing seventeen other systems first. Real talk: most trading algorithms fail because they’re built for perfect market conditions. Crypto markets are anything but perfect. Think about it like this. Would you trust a Formula 1 car to handle rush hour traffic? That’s essentially what most people do with their trading bots. Why Smart Money Uses Crypto AI Tools Differently Professional traders approach crypto AI tools with surgical precision. They don’t expect miracles. They expect consistent, measured results. The difference lies in understanding what these tools actually do well: • Risk management automation • Pattern recognition at scale • Emotional bias elimination • 24/7 market monitoring • Portfolio rebalancing Notice what’s missing from that list? Get-rich-quick schemes. The smartest crypto AI tools focus on protecting capital first. Profits come second. This mindset separates winners from losers. Here’s something interesting. 9-figure media companies track these patterns religiously. They know which crypto AI tools produce sustainable results versus flashy short-term gains. Professional traders using crypto AI tools typically target 15–25% annual returns. Not 500% monthly moonshots. The Startup Connection Most People Ignore AI for startups isn’t just about building the next ChatGPT. Many successful companies use AI to optimize their crypto treasury management. Smart startups integrate crypto AI tools into their financial operations early. They automate routine decisions. They reduce human error. They scale their trading operations without hiring armies of analysts. But here’s where it gets interesting. The best AI for startup applications in crypto aren’t the obvious ones. Consider automated tax reporting. Or real-time compliance monitoring. Or treasury optimization across multiple blockchains. These unsexy applications generate more consistent profits than flashy trading algorithms. AI for startups in the crypto space succeeds when it solves boring problems efficiently. Not when it promises unrealistic returns. The most successful AI for startups implementations focus on operational efficiency. They reduce costs. They minimize risks. They free up human resources for strategic decisions. Learning from Top AI Start-Ups Top AI start-ups in the crypto space share common characteristics. They prioritize transparency over marketing hype. Look at successful top AI start-ups like Chainalysis or Elliptic. They don’t promise easy money. They provide essential infrastructure. The best top AI start-ups focus on solving real problems: • Market data analysis • Security monitoring • Regulatory compliance • Portfolio analytics • Risk assessment These top AI start-ups understand something crucial. Sustainable businesses solve actual problems. They don’t just ride hype cycles. 9-figure media outlets consistently highlight these fundamental companies. They ignore the noise. They focus on substance. Many top AI start-ups actually discourage retail trading. They know the odds. They’ve seen the casualties. Instead, successful top AI start-ups build tools for institutions. Banks. Hedge funds. Companies with proper risk management systems. The Hidden Costs Nobody Discusses Using crypto AI tools costs more than subscription fees. Much more. First, there’s the learning curve. Most people spend months figuring out proper settings. During this time, they’re paying tuition to the market. Second, there’s infrastructure. Reliable crypto AI tools require stable internet, backup systems, and proper security measures. Third, there’s opportunity cost. Time spent tweaking algorithms could be spent learning fundamental analysis. The real cost? Most people using crypto AI tools trade more frequently. Increased trading usually means increased losses. Think about 9-figure media companies again. They understand that technology amplifies existing skills. It doesn’t replace them. Smart Implementation Strategies Successful crypto AI tools users follow specific patterns: • Start with paper trading • Use position sizing rules • Set strict stop losses • Monitor performance weekly • Adjust strategies quarterly They treat crypto AI tools like any other business tool. With respect. With caution. With realistic expectations, startup applications work similarly. They augment human decision-making. They don’t replace it. The most successful AI for startups implementations in crypto involve human oversight at every level. Algorithms suggest. Humans decide. What Actually Works Here’s what separates successful crypto AI tools users from everyone else: They focus on consistency over home runs. They understand that small, regular gains compound better than occasional big wins followed by devastating losses. They apply AI principles to their approach for startups. They iterate quickly. They fail fast. They learn constantly. They study top AI start-ups for inspiration. But they don’t try to replicate their exact strategies. Most importantly, they never risk money they can’t afford to lose. The crypto market will humble anyone. AI doesn’t change this fundamental truth. Your success with crypto AI tools depends more on your discipline than the sophistication of your algorithms. Remember: the house always has an edge. Your job is to find where that edge doesn’t apply. That’s the secret they won’t tell you. AI Crypto Trading Secrets: What They Won’t Tell You About Profits and Pitfalls|9-Figure Media was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story
Share
Medium2025/09/18 23:20