🧠 Truth and AI: An Unlikely Alliance

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Welcome back AI prodigies!

In today’s Sunday Special:

• 🧩The Truth is Hard to Come By

• 🤖Is AI Our Savior?

• ⚔️Google Versus Consensus

• 💥Bonus Tip: Optimize Consensus Prompts

Read Time: 6 minutes

Disclaimer

The AI Pulse has no affiliation with Consensus. The following newsletter is a voluntary, no-strings-attached exploration of Consensus’s search tool. We aim to highlight the importance of objective truth in the information age and Consensus’s value proposition versus competing search offerings.

🧩THE TRUTH IS HARD TO COME BY

The truth has been elusive for as long as the sky has been blue. Still, some truths are easier to establish, propagate, and accept than others. Objective truths, at least according to philosophical realists, exist regardless of how anyone perceives them. In other words, objective truth is not in the eye of the beholder; for instance, it’s objectively true that the Earth revolves around the Sun. But we often crave answers to murkier or open-ended questions: Does spanking impact childhood development? Does poverty cause crime? Does lowering taxes increase economic growth? What are the benefits of meditation? Objective answers may be what we’re after, yet more often than not, what we feel to be true is inherently subjective.

Subjective truths exist in the eyes of the beholder; for instance, I feel like intelligence is purely genetic. Somewhere in the middle lies normative truth, which are subjective truths that groups agree on; for instance, Kanye West, given his latest fiascos, is irredeemable.

Regardless of dataset quality, parameter quantity, fine-tuning, etc., algorithms cannot intelligently wrestle with subjective or normative truths. Although today’s models are increasingly more precise, we cannot intentionally encode the “right” mix of human bias into a machine-learning model. Since we don’t fully understand the complex sources of bias, we can’t replicate its pervasive effect on truth-finding.

🤖IS AI OUR SAVIOR?

We now turn to the relationship between objective truths and AI. Can AI bring us a world teeming with, not sparsely populated by, objective truth? Not directly, at least not yet. Models are only as good as their assumptions. The best tool we have to produce reliable knowledge is the scientific method. Of course, only researchers on the front lines of knowledge production are privy to the process, nuances, and limitations of establishing objective truth. The rest of us often consume garbage processed and recycled by media outlets, social media algorithms, and content creators. They maximize engagement, retention, and other so-called KPIs, which the technocratic class worships. And scientists tend to present their findings in exclusive, elite spaces—institutes, academies, board rooms, and the like. And if the heads of three-letter agencies dare to share science-based recommendations, they’ll likely do more harm than good. If tomorrow the CDC declared a pandemic due to a novel virus with a death rate of 10% (at least 100 times more deadly than COVID-19), a quarter of Americans wouldn’t believe them.

AI, specifically large-language models (LLMs), circumvents the media middleman. But not via text-generating, hallucinating chatbots. Humans are the most robust BS detectors. LLMs, like Consensus, can parse scientific journals to provide evidence-based answers to pressing questions in plain English.

⚔️GOOGLE VERSUS CONSENSUS

📊Google

Let’s examine one of the queries posed earlier: “What are the benefits of mindfulness meditation?”

Google Search spits out a “featured snippet” from a reputable source (Mayo Clinic):

Google Bard provides a summary of benefits. Since it generates original content, it fails to cite sources:

What about a more involved query like “Does spanking impact childhood development?” Chatbots aren’t even worth trying.

Again, Google provides an answer from a reputable source. However, the plain English answer relies solely on the latest research. It also spits out research publications, but deriving any benefit requires parsing through the Abstract, Data, Results, and Conclusion sections.

Competing chatbots such as Claude2 and Llama 2 specialize in dialogue, not information retrieval. Nevertheless, Google Search seems adequate, as it makes credible information accessible. But for less common scientific questions, Search falls short.

🧬Consensus

Consensus produces similar answers but with direct citations. Double-click on each study and replicate the exact meditation practices of research participants to increase your probability of realizing the intended benefit. The results are more detailed and practical, but certainly not life-changing.

Consensus is clearly more comprehensive with its GPT-4-powered summaries. It gives you the agency to explore the nuances of multiple studies. For instance, one study focuses on spanking in diverse populations (Black and Hispanic children). Further, the Consensus Meter answers yes or no questions probabilistically, given ample quality publications:

✏️BONUS TIP: OPTIMIZE CONSENSUS PROMPTS

Optimal Queries Ask:

• Simple Yes or No Questions → Consensus Meter

• About the Impact, Effect, Benefits, or Drawbacks of a Concept → GPT-4-Powered Summary

Less Optimal Queries Ask:

• For a Specific Number (Hit or Miss)

• For the Best Something (Too Subjective)

• How to Do Something (Unscientific Language)

• Two Concepts Are Separated by “and” (Too Vague)

💥CONCLUSION

Consensus combines the user-friendliness of ChatGPT, the scientific rigor of top journals, and the breadth of Google Search. The next time you have a question (that scientists have likely researched), skip Search, bypass "the experts," and go straight to the studies.

📒FINAL NOTE

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