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Shallow assumptions about complex topics are the bane of AI summary tools

Skimming articles and using quick AI-generated summaries is killing my ability, and yours, to understand complex topics. While the shortcut offers headline-level comprehension, it often miss vital details from primary sources. Instead of depending on summaries or (shudder) listicles and quick-hit videos, I’ve learned to prioritize original source material whenever possible.

The Illusion of Understanding

It’s easy for me to feel informed by high-level summaries, especially those generated by AI. I can quickly skim articles and think I’m up to speed, but these summaries often lack the depth and nuance needed for real understanding. When these summaries are widely syndicated, incorrect assumptions take on an undeserved authority, and I find myself accepting without question. The problem gets worse when these summaries are cited as evidence, further distancing us from the original material.

Why AI Summaries Can Mislead

AI-generated summaries are built for speed and convenience. Unless I specifically prompt tools for critical evaluation, they rarely highlight methodological flaws or contextual limitations. The result? I end up making assumptions based on oversimplified information and missing key points that are present in the primary sources.

Case in Point: AI’s Impact on Jobs

A recent study about generative AI’s effect on jobs is a perfect example. At first glance, the headlines suggested an immediate threat to workers, especially women. But when I dug into the original study, I found a lot of assumptions baked in. For starters, the research was conducted in just one country, Poland, yet the conclusions were extrapolated globally. Respondents were asked to self-evaluate the impact of AI on their jobs, even when their expertise was limited. There were also clear gender and occupational disparities in the roles surveyed.

This is a problem. Unrepresentative samples, limited respondent expertise, and global extrapolations mean the study’s conclusions should be viewed critically. The source material actually acknowledges these limitations and calls for further study. If I had just skimmed the headline and reposted it, I’d be jumping to conclusions and missing the fact that, while not definitive, this topic deserves much deeper investigation.

What I Do Instead

Consult Primary Sources

To avoid making incorrect assumptions, I make a point to consult primary sources whenever possible. Not only do I get a more accurate understanding, but I can also evaluate the evidence, context, and limitations behind any claim. If I truly care about a subject, it’s worth drilling down to find the original study or data.

Skim, But Don’t React

Summaries and lists are great for a quick overview, but they’re often designed to provoke an emotional reaction. If I take a post at face value and respond immediately, I risk lending credibility to misinformation and unwarranted assumptions. Instead, I use summaries to get a high-level overview, then selectively dig into the items that seem most important. If I can’t find any primary sources, I assume the article is probably B.S., even AI-generated content has a source if you look hard enough.

Better AI Summaries

A lot of sites and services claim to provide insightful AI summaries. Over the past year, I’ve tried many, and most are limited by the quality and depth of their source data. Worse, some tools only summarize headlines and publicly available summary articles, creating the illusion of being informed when, in reality, I’m just being marketed to.

Rather than rely on AI to aggregate sources, I subscribe to a selection of newsletters and RSS feeds that bring fresh articles. These are mostly human-curated, and when I notice a headline appearing across several sources, I take it as a sign of importance. But I’m busy, so how do I dig into the details?

Digging In

In short, I start clicking. Before I dive in, I often use Perplexity as a first-pass summary tool. This isn’t a Perplexity advertisement, paid or otherwise, just my opinion of the best tool for the job right now.

Perplexity’s research feature stands out because it breaks down queries, conducts dozens of targeted searches, and evaluates hundreds of sources in real time. By prioritizing authoritative and reputable sources, it generates summaries with citations to the original material.

Another advantage I’ve found is that I can upload the original study (as a PDF) and ask Perplexity to research and summarize it further. This feature is incredibly useful, as it not only condenses long documents but also cites specific sections of the source material.

Takeaway