AI ‘ghosts’ can comfort mourners  even when the bots get the facts wrong 66%

By Kathryn Hulick39%

7/20/2026, 3:00:00 PM

BS Summary: This article contains 21 faulty reasoning types, including Availability Heuristic, Hasty Generalization, and Optimism Bias, with Anecdotal as the most egregious example at 23.3% saturation with 109 hits. Analysis detected 784 faulty-reasoning hits from 468 analyzed words, generating a BS Score of 60.4% and a BS Rank of 66% (6,985 of 20,377 articles). This article is worse (more manipulative) than 65.70% of the article peer group.

Manning, of the University of Colorado Boulder, was very surprised by how much the volunteers enjoyed speaking to the AI-generated ghosts. 
“They love this technology,” he says. 
His 13-year-old sister had died when he was 11. 
Now, he feels a strong aversion to the idea of talking with her digital ghost. 
“I have a version of my sister in my head,” he says. 
“I wouldn’t want to be confronted with the fact that maybe I’m wrong in my way of remembering her.” 
His study volunteers, however, “clearly came with a goal in mind,” Manning says. 
“They had a question they felt was unanswered or a detail in their life they were desperate to share.” 
People who did not want to interact with a re-creation of a deceased loved one were not included. 
Across the board, volunteers reported the experience was positive. 
“It felt like I was actually talking with my grandpa,” one participant told researchers. 
Another said, “It just feels like I’m getting the closure I needed so bad.” 
The only information the chatbot had to draw on for its impersonation was a brief survey that the participant had completed about their deceased loved one. 
And when the bot filled in missing details with fabrications, such as mentioning a job someone never held, participants often just plowed forward. 
Mistakes in tone or style bothered them much more. 
For example, the bot never used emojis  a small omission that mattered to participants who had mostly communicated with their loved ones by text. 
In another case, a bot called a participant “champ,” a name he said his loved one never would have used. 
“If we want to understand how to design these systems ethically, we need more evidence of this kind,” says AI ethicist Tomasz Hollanek of the University of Cambridge, who was not involved in the research. 
The study had guardrails. 
A human researcher mediated each conversation, reviewing the chatbot’s replies before passing them to participants. 
That helped prevent interactions that might be deceptive or harmful. 
The real world is messier. 
Anyone can prompt a chatbot to impersonate someone who has died, and companies now sell services that recreate loved ones through AI-generated text, voices or faces. 
Study participants saw the risks. 
One worried about becoming too reliant on conversations with the bot. 
Another said, “I don’t know if I would like the person I would become if I kept using this.” 
The lack of consistent guardrails in the real world concerns Manning. 
But the study also softened his own aversion to AI-generated ghosts. 
Designed carefully, the technology might help some people work through grief, he says. 
“There is a version of generative ghosts that could be a really positive thing in the world.” 
Article reasoning-pattern comparisonThis article: 8.5%Kathryn Hulick: 3.1%Science News: 2.6%Confirmation Bias8.5%This article: 0.0%Kathryn Hulick: 0.2%Science News: 1.0%Anchoring Bias0.0%This article: 21.4%Kathryn Hulick: 4.9%Science News: 2.5%Availability Heuristic21.4%This article: 5.3%Kathryn Hulick: 1.6%Science News: 1.4%Representativeness Heuristic5.3%This article: 0.0%Kathryn Hulick: 0.6%Science News: 0.5%Hindsight Bias0.0%This article: 0.0%Kathryn Hulick: 1.0%Science News: 2.4%Overconfidence Bias0.0%This article: 3.0%Kathryn Hulick: 3.6%Science News: 4.3%Framing Effect3.0%This article: 7.3%Kathryn Hulick: 1.5%Science News: 0.3%Loss Aversion7.3%This article: 0.0%Kathryn Hulick: 0.1%Science News: 0.2%Status Quo Bias0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.2%Sunk Cost Effect0.0%This article: 12.6%Kathryn Hulick: 2.4%Science News: 4.3%Optimism Bias12.6%This article: 8.3%Kathryn Hulick: 1.2%Science News: 1.3%Pessimism Bias8.3%This article: 6.2%Kathryn Hulick: 4.9%Science News: 4.1%Negativity Bias6.2%This article: 0.0%Kathryn Hulick: 0.5%Science News: 0.4%Self-Serving Bias0.0%This article: 5.6%Kathryn Hulick: 1.5%Science News: 0.5%Fundamental Attribution Error5.6%This article: 2.4%Kathryn Hulick: 0.4%Science News: 0.1%Actor-Observer Bias2.4%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.1%In-Group Bias0.0%This article: 0.0%Kathryn Hulick: 0.2%Science News: 0.1%Out-Group Homogeneity Bias0.0%This article: 4.3%Kathryn Hulick: 0.9%Science News: 1.4%Halo Effect4.3%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Horn Effect0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Kathryn Hulick: 2.2%Science News: 0.8%Recency Bias0.0%This article: 0.0%Kathryn Hulick: 0.3%Science News: 0.3%Primacy Effect0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Blind-Spot Bias0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.2%Ad Hominem0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.1%Straw Man0.0%This article: 7.5%Kathryn Hulick: 6.4%Science News: 4.6%Appeal to Authority7.5%This article: 0.0%Kathryn Hulick: 1.9%Science News: 1.1%False Dilemma0.0%This article: 1.1%Kathryn Hulick: 4.2%Science News: 1.2%Slippery Slope1.1%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.1%Circular Reasoning0.0%This article: 16.2%Kathryn Hulick: 6.2%Science News: 4.0%Hasty Generalization16.2%This article: 0.0%Kathryn Hulick: 0.1%Science News: 0.0%Red Herring0.0%This article: 0.0%Kathryn Hulick: 1.0%Science News: 0.3%Bandwagon0.0%This article: 7.1%Kathryn Hulick: 1.9%Science News: 2.6%Appeal to Emotion7.1%This article: 0.0%Kathryn Hulick: 0.2%Science News: 0.5%Begging the Question0.0%This article: 4.5%Kathryn Hulick: 4.0%Science News: 2.5%Post Hoc (False Cause)4.5%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Tu Quoque0.0%This article: 2.8%Kathryn Hulick: 1.1%Science News: 0.4%Burden of Proof2.8%This article: 0.0%Kathryn Hulick: 0.4%Science News: 0.2%Appeal to Nature0.0%This article: 0.0%Kathryn Hulick: 0.5%Science News: 0.2%Composition/Division0.0%This article: 23.3%Kathryn Hulick: 4.4%Science News: 1.2%Anecdotal23.3%This article: 0.0%Kathryn Hulick: 0.4%Science News: 0.1%No True Scotsman0.0%This article: 11.8%Kathryn Hulick: 3.5%Science News: 1.6%Ambiguity (Equivocation)11.8%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Kathryn Hulick: 0.3%Science News: 0.2%Middle Ground0.0%This article: 0.0%Kathryn Hulick: 0.1%Science News: 0.1%Personal Incredulity0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Special Pleading0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.0%Genetic Fallacy0.0%This article: 0.0%Kathryn Hulick: 1.0%Science News: 0.8%Unattributed Quote0.0%This article: 0.0%Kathryn Hulick: 0.2%Science News: 0.6%Quote-first Misdirection0.0%This article: 3.0%Kathryn Hulick: 1.3%Science News: 2.7%Biased Writer Voice3.0%This article: 0.0%Kathryn Hulick: 2.8%Science News: 0.9%Indoctrination0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.4%Politically Left Leaning Bias0.0%This article: 0.0%Kathryn Hulick: 0.0%Science News: 0.1%Politically Right Leaning Bias0.0%This article: 5.6%Kathryn Hulick: 0.2%Science News: 0.4%Attempt to Sell a Product or S…5.6%

468 words analyzed.

Speakers

2speakers32%attributed speech319writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 14 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageManning • 6 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageManning • 15 words • 0.0% coverageManning • 12 words • 0.0% coverageManning • 19 words • 0.0% coverageManning • 13 words • 0.0% coverageManning • 19 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageTomasz Hollanek • 35 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 26 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageManning • 13 words • 0.0% coverageManning • 17 words • 0.0% coverage
Selected voice

Manning

100%flagged-word coverage
114 attributed words77% of attributed speech92% writer coverage
0%5.0%10.0%Attempt to Sell a Product -8.2 ptsWriter: 8.2%Manning: 0.0%0.0%Biased Writer Voice-4.4 ptsWriter: 4.4%Manning: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.