Summaries You Can Trust
Learn how AI summaries go wrong and how to check one in a few minutes before you rely on it.
A taste of a lesson
The summary said a study proved remote work increases productivity. The paper itself seemed less sure. Who is right?
Trust the paper. This is a classic distortion: careful language like 'was associated with' or 'in our sample' becomes 'proved'. Summaries often drop limitations because they look like detail. Next time ask: 'Summarise the main finding using the authors' own level of certainty, and list the limitations they state, with page numbers.' Then read the limitations section yourself. Quick exercise: find one sentence in the paper where the authors qualify their finding, and compare it with the summary's wording.
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Name the common ways AI summaries distort or drop information
- Write summary prompts tied to a purpose with references to the source
- Check a summary against its source in about five minutes
- Judge when a document must be read in full instead
Lesson plan
- 1 How summaries go wrong Recognise omission, distortion, invention and number errors. Start
- 2 Purpose driven summary prompts Ask for summaries shaped around the decision they support. Start
- 3 References back to the source Make each point in a summary traceable. Start
- 4 The five minute check Verify a summary quickly before relying on it. Start
- 5 Length and stakes Choose summary length and checking effort by risk. Start
- 6 When to read the original Know which documents should not be judged from a summary. Start
Try asking
About this tutor
Summaries are the most common thing people ask an assistant for, and the easiest to trust too much. A summary can drop a key exception, turn 'may' into 'will', swap a number or invent a conclusion the author never drew. This tutor teaches you the typical failure patterns, how to write summary prompts tied to a purpose, how to ask for references back to the source, and a quick checking routine for reports, articles, policies and long threads. You also learn when not to rely on a summary at all. For people who already use assistants and want to depend on them more safely.
Reviews
4.0
3 ratingsSample
- Yasmin K.Sample
Good content, though I hoped for more on summarising video or audio, which is most of what I deal with.
- Olga D.Sample
I write briefings for directors. The 'keep the hedges' instruction and the number check changed how much I trust and verify.
- Samuel A.Sample
Concrete examples of distortion made it click. A bit repetitive in the last lesson but overall very useful.
About the teacher
Careful, practical use of AI assistants for everyday office work: email, meetings, files and team habits
9 tutors 332 lessons taught Sample
I help office teams use chat assistants for the work that fills a normal week: email, meeting notes, summaries, documents and translation. I spent a long stretch in administration and internal communications, so I know how much of a job is reading, condensing and replying. My teaching is hands on and cautious in equal measure. We practise on realistic tasks,...
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