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How the Wealth Was Won: Factor Shares as Market Fundamentals | Journal of Political Economy: Vol 133, No 4

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Babies and toddlers referred to Prevent hundreds of times - Hyphen

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A baby's hand poking out of a red sleeve, visible from behind as it sticks out of a buggyChildren less than a year old have been referred to Prevent with referrers citing ‘Islamist’ concerns, data obtained by Hyphen reveals. Stock photograph by combo1982/Getty Images

Babies and toddlers have been referred to the government’s controversial counter-terrorism scheme Prevent hundreds of times since 2016, Hyphen can reveal. 

Infants who had not yet turned two were referred to Prevent 86 times between 2016-17 and 2023-24 — with more than two-thirds (59) of these referrals over so-called “Islamist” concerns, data obtained by this website shows.

Children aged two to five, inclusive, were referred to Prevent a further 500 times over this eight-year period.

Alexander Gent, the chair of the National Association of Muslim Police, said he was “absolutely shocked” by our findings.

The human rights charity Rights & Security International raised concerns earlier this year that the personal data of those referred to Prevent may be being duplicated across a “convoluted spider’s web” of publicly administered databases, where it may remain visible to police, immigration authorities and other agencies even after the initial entry has been deleted.

“These figures are deeply concerning and raise serious questions about how Prevent is operating,” said Liberal Democrat education spokesperson and Twickenham MP Munira Wilson.

“In its current form, Prevent does not seem to be the right way to protect vulnerable children from terrorism or extremism.

“The government must ensure that the Prevent commissioner takes a comprehensive look at Prevent and that any future approach is genuinely community-led and focused on safeguarding.”

The Home Office said that in the “rare instances where a young child has been exposed to harmful terrorist narratives, early intervention through Prevent can provide vital safeguarding measures”.

What is the Prevent duty?

Prevent, part of the government’s wider Contest counter-terrorism strategy, has a stated aim of safeguarding people from “becoming terrorists or supporting terrorism”.

The scheme places a duty on specified authorities in England, Wales and Scotland to report people if they are deemed “at risk of being drawn into terrorism”. Teachers, doctors, police officers and council workers are among those subject to the Prevent duty.

Reports to Prevent are assessed by police and councils and may be escalated to the government’s Channel programme, which decides whether to intervene and can develop “support” plans. Campaign groups warn that such referrals have led to people losing out on sixth form and university places and housing.

The government publishes annual Prevent figures, but uses wide age brackets for those referred to the scheme. The data obtained by Hyphen has never before been revealed in this level of detail. It shows the number of Prevent referrals, not individuals referred, meaning some may have been referred more than once.

Baroness Shaista Gohir, chief executive of the Muslim Women’s Network UK, said referrals of very young children could well be linked to suspicions about their parents or older siblings. 

“I am deeply shocked,” she said, adding that she was concerned the implications of a referral could be “around their neck for the rest of their life”.

“These children are being stereotyped and labelled when they are innocent children,” she said, “and I do worry, and it’s a genuine concern, that that does stay with them.”

Rights & Security International warned in January that, while “official policy says the police must usually delete data stored on the designated Prevent database after six years, the data can remain in other databases indefinitely — risking real long-term impacts on the person referred, including children who have since become adults”.

The Home Office said it “strongly rejected the conclusions” of this report in January: “Data on individuals at risk of being drawn into terrorism is held by the police only temporarily, and parents or carers can request its deletion earlier, if appropriate. All data is kept strictly confidential, except where a serious security risk arises. The Home Office does not maintain these individuals on watchlists.”

Nearly half (46%) of the Prevent referrals for kids aged 10 or under during this period were for “Islamist” concerns. But this figure jumps to 70% for the youngest kids — those aged three or under.

Gent told Hyphen: “I struggle to understand how this applies to someone so young, especially for children who are babies and can’t even speak or even comprehend what an extremist ideology is.”

The Home Office said all referrals are “carefully assessed” by the police and local councils to see if they are suitable for its Channel “early support” and intervention programme. 

The department added that: “All referrals to Prevent are carefully assessed based on the specific details of the case.

“If a child is found to not be at risk of radicalisation, the case is immediately closed to Prevent. They may be referred to other appropriate services, or no further action may be taken.”

Other Prevent referral categories include “extreme right-wing” and “incel extremism”.

The Home Office last week published data showing that, in the year to March 2025, there were 8,778 referrals relating to 8,517 people.

This was up 27% year-on-year and is the highest number of referrals recorded in a single year since records began in 2015, it said.

Has a Prevent referral negatively affected you or someone you know? Contact Lucas Cumiskey by emailing <a href="mailto:lucas.cumiskey@hyphenonline.com">lucas.cumiskey@hyphenonline.com</a>.

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no less beautiful for our variation | MetaFilter

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no less beautiful for our variation
October 13, 2025 12:37 PM   Subscribe

 

« Older Comic Book Burnings Project   |   "Without truth, there can be no reconciliation" Newer »

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‘Mensen met ernstige psychiatrische aandoeningen maken na vaccinaties minder antistoffen aan’ - NRC

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Deze kans krijg ik maar één keer, dacht psychiater en onderzoeker Livia De Picker (37) toen haar patiënten aan de beurt waren voor de coronavaccinaties in mei 2021. De pandemie was in volle gang, en ze werkte nog maar pas in het Universitair Psychiatrisch Centrum Duffel in België. Uit China kwamen berichten dat mentaal kwetsbare mensen ernstiger ziek worden van het virus en er vaker aan overlijden dan mensen zonder die problemen. Ze had met succes campagne gevoerd om psychiatrische patiënten voorrang te geven bij de Europese vaccinatie-uitrol.

Al langer vermoedde ze dat het immuunsysteem bij psychiatrische patiënten verstoord is. En nu kon ze dat testen.

In één van de modernere gebouwen op het terrein van de kliniek midden in Duffel, waar haar lab huist, zet De Picker in haar kantoor het stabureau wat lager. Ze vertelt over de studie die ze in de pandemie opzette. „We namen bij de patiënten en bij het personeel bloed af vóór en na de eerste vaccinatie, en voor en na de tweede vaccinatie. En wat bleek: mensen met ernstige psychiatrische aandoeningen, zoals zware depressie, schizofrenie of een psychose, maken minder antistoffen aan na vaccinaties. Hun afweersysteem lijkt ontregeld.”

De Picker promoveerde in 2020 op onderzoek naar psychose en ontsteking. „Toen was ik nog sceptisch over de relatie, maar toen ik hier als psychiater aan de slag ging, zag ik steeds duidelijker verbanden bij mijn patiënten. Er is bijvoorbeeld een subtype van depressie, dat immuungedreven lijkt.” Haar onderzoek is in september bekroond met een prijs van het populair-wetenschappelijke tijdschrift EOS Psyche & Brein.

Wat is er verstoord in de afweer van mensen met psychiatrische aandoeningen?

„In onze studie zagen we dat bij psychiatrische patiënten de eerste linie van het immuunsysteem overactief is. Dat is de aangeboren afweer, de snelle, brede verdediging tegen infecties. De tweede verdedigingslinie, die enkele weken later op gang komt, is juist zwakker. Dat is de verworven afweer, met specifiek op de ziekteverwekker gerichte antistoffen.”

Is een psychiatrische aandoening een oorzaak of een gevolg van een verstoord immuunsysteem?

„Het kan in beide richtingen gaan. Ik ben ondertussen redelijk zeker van een causaal effect. Een verstoord immuunsysteem kan depressie veroorzaken. Dat weten we uit grote langlopende studies, maar ook dankzij behandelingen. Als je vroeger mensen bijvoorbeeld tegen hepatitis C behandelde met interferon om hun immuunsysteem aan te wakkeren, kreeg ongeveer een derde depressie.

„We zien een subgroep bij depressie, met atypische klachten. Bij deze patiënten domineert een uitgesproken vermoeidheid. Ze kunnen het niet opbrengen om iets te gaan doen. Anders dan bij andere vormen van depressie is bij hen de eetlust juist toegenomen, hun gewicht neemt toe, ze hebben opmerkelijk meer nood aan slaap. En behandeling met antidepressiva helpt bij hen niet goed.

„Bij dit subtype is er vermoedelijk een immunologische ontregeling, het hangt samen met verhoogde ontstekingswaarden. De groep van hoogleraar psychiatrische epidemiologie Brenda Penninx in Amsterdam heeft hier veel onderzoek aan gedaan. Een derde van de mensen met een depressie valt in deze subgroep.”

Livia De Picker.

Foto Ans Brys

Hoe leidt zo’n ontregeling tot psychische klachten?

„Van de stoffen die de cellen in de eerste verdedigingslinie uitscheiden, cytokines, worden mensen moe, hangerig, down. Dat ziektegedrag is gunstig bij een infectie, zo kan het lichaam alle energie gebruiken voor de afweer. Normaal gesproken kalmeert die tak van de afweer als de infectie bedwongen is. Er zijn aanwijzingen dat bij sommige psychiatrische patiënten dit deel van de afweer overactief blijft, en een chronische, laaggradige ontsteking in stand houdt.

„Ontstekingsstoffen activeren in de hersenen de lokale immuuncellen, microglia. Die richten zich dan minder op het dagelijkse herstel en onderhoud van hersencellen. Ze beïnvloeden ook de productie van belangrijke signaalstoffen die een rol spelen bij energie, motivatie en stemming, zoals dopamine en serotonine.”

Waardoor raakt de afweer zo verstoord?

„Dat kan door allerlei dingen komen. Door een slechte leefstijl bijvoorbeeld. Of door een auto-immuun­aandoening. Mensen met bijvoorbeeld psoriasis, diabetes type 1 of reuma lopen een hoger risico op psychiatrische aandoeningen, zoals depressie. En andersom: als we die auto-immuunziekte behandelen, vermindert de depressie vaak.

„Een derde route zijn infecties. Dat werd heel duidelijk bij covid. En dat zien we bij alle infecties, een groep mensen die langdurige klachten zoals depressie, angst of slaapproblemen houdt. Ongeveer 1 op 3 mensen is daar gevoelig voor, denken we. De grote fout bij het chronisch vermoeidheidssyndroom, ME/CVS, is dat men te lang op zoek was naar het éne virus dat het veroorzaakt. Maar elke infectie kan dat triggeren. Of wellicht een herhaaldelijke blootstelling aan infecties. Mensen die als kind vaak met infecties in het ziekenhuis lagen, hebben later een hoger risico op een psychiatrische aandoening, blijkt uit een grote Scandinavische studie.”

De helft van de proefpersonen lieten we een stresstest doen: hardop moeilijke hoofdrekensommen maken tegenover drie streng kijkende onderzoekers in witte jassen

Speelt stress ook een rol bij die immuundepressie?

„Stress kan een depressie tijdelijk aanwakkeren. Wij denken doordat het interfereert met die eerste linie van de afweerreactie.  Wij hebben een studie gedaan met mensen die in het verleden een depressie hadden, en vrijwilligers zonder depressieverleden. Zij kregen een vaccinatie tegen tyfus, om hun immuunreactie te prikkelen, óf een placebo. De helft van de proefpersonen lieten we daarna direct een stresstest doen: hardop moeilijke hoofdrekensommen maken tegenover drie streng kijkende onderzoekers in witte jassen.

„Enkel bij de mensen met een voorgeschiedenis van depressie zagen we na die dosis stress na de vaccinatie, de tijdelijke immuunactivatie, een tijdelijke dip in stemming. Je kunt je voorstellen dat als die immuunactivatie chronisch aanwezig is, dat blijvend invloed op de stemming kan hebben, telkens wanneer je met stress te maken krijgt.”

Moeten mensen met deze vorm van depressie ontstekingsremmers slikken?

„We hebben nog niet genoeg wetenschappelijk bewijs om dit op grote schaal toe te passen. Wij doen nu een studie met 240 patiënten met depressie, we zoeken nog deelnemers. We delen hen in op basis van een ontstekingsmaat in het bloed: het eiwit CRP. Het is al eerder gezien dat mensen met depressie bij wie het CRP verhoogd is, minder goed reageren op een behandeling met antidepressiva. Elke deelnemer krijgt, zonder dat ze weten welke, een van drie behandelingen toegewezen: met celecoxib, een ontstekingsremmende pijnstiller. Met minocycline, een antibioticum dat immuuncellen in het brein stabiliseert. Of met een placebo. Vanaf 2028 zullen we de resultaten hebben. In Amsterdam loopt een vergelijkbare studie.”

Hoe reageren psychiaters op uw bevindingen?

„Op congressen zit de zaal vol als ik lezingen geef, zeker jonge collega’s zijn enthousiast. Maar andere psychiaters en psychologen zijn nog sceptisch. Vanuit hun optiek domineren ofwel psychologische oorzaken, of sociale of biologische. Maar in realiteit beïnvloeden natuurlijk bij elke psychiatrische aandoening al die dingen elkaar.  Omgekeerd sturen neurologen en internisten patiënten met klachten bij wie ze niets kunnen vinden vaak te snel door naar psychiaters omdat ze denken dat het dan psychisch is.”

En wat vinden patiënten ervan?

„Die zijn heel positief; er is eindelijk een mogelijke biologische verklaring voor wat ze ervaren. Een collega in het Verenigd Koninkrijk, die een immuunbehandeling voor psychiatrische problemen aanbiedt, wordt zelfs overstelpt door patiënten. Begrijpelijk, er rust nog altijd een stigma op psychiatrische aandoeningen. Het wordt vaak gezien als een zwakte, een persoonlijk falen. Een ontregeld immuunsysteem als mogelijke oorzaak maakt het in hun ogen een écht medisch probleem. Terwijl natuurlijk alle psychiatrische aandoeningen echt zijn, of ze nu aan het immuunsysteem te wijten zijn of niet.”

Wat doet u zelf om mentaal gezond te blijven?

„Ik werk altijd aan een stabureau. En ik ben sinds de pandemie begonnen met krachttraining en hardlopen – niet te intensief hoor, rondjes van vijf, tien kilometer. Na lopen ben ik moe, maar na een ronde gewichtheffen heb ik méér energie dan ervoor!

„En ik heb nog iets belangrijks aangepast. Als ik een infectie doormaak, al is het een verkoudheid, neem ik het bij het eerste signaal onmiddellijk rust, tot ik voel dat die moemakende afweerreactie helemaal verdwenen is. Dat lethargische gevoel is de boodschap van je immuunsysteem: spaar je energie, die heb ik nu nodig. Niet de schouders eronder en doorbijten. Luisteren naar je lichaam.”

Foto Ans Brys

NIEUW: Geef dit artikel cadeau Als NRC-abonnee kun je elke maand 10 artikelen cadeau geven aan iemand zonder NRC-abonnement. De ontvanger kan het artikel direct lezen, zonder betaalmuur.

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Light pollution: The silent threat to the planet that's easily solved

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light pollution Credit: Unsplash/CC0 Public Domain

New research has revealed for the first time the full extent of how "Artificial Light At Night" (ALAN) is increasing carbon released by plants and animals across continents—without any increase in the carbon they absorb. The result is reduced carbon storage in ecosystems—which has major implications for climate models and global carbon budgets.

Artificial light at night is reshaping carbon balance of whole ecosystems

The study, "Widespread influence of artificial light at night on ecosystem metabolism"</i> published in Nature Climate Change by researchers at Cranfield University, is the first to demonstrate how ALAN is silently reshaping the carbon balance of ecosystems across entire continents.

The research team found that light pollution at night increases ecosystem respiration—when plants, microbes, and animals release carbon dioxide through activity and growth—but that there was no corresponding increase in photosynthesis, the process that removes carbon dioxide from the atmosphere.

Conducted with data from satellite observations and 86 carbon flux monitoring sites across North America and Europe, the study reveals that the effects of ALAN scale up to alter continental patterns of carbon outputs and absorption, negatively affecting whole ecosystems.

"Light pollution is one of humanity's most visible environmental changes, but its impacts are often hidden," said Dr. Alice Johnston, Senior Lecturer in Environmental Data Science at Cranfield University, who led the research.

"This is a widespread issue that's changing how ecosystems function, disrupting energy flows, animal behavior, habitats and natural patterns. Put simply, brighter nights lead to greater carbon release, which is bad news for our planet."

"Around a quarter of Earth's land surface now experiences some level of artificial illumination at night," said Jim Harris, Professor of Environmental Technology and co-author of the study. "Our findings suggest that this growing footprint could subtly but significantly shift the global carbon balance if left unaddressed."

Climate models should include light pollution

Artificial light is one of the fastest-growing pollutants on the planet, increasing in radiance and extent across the land surface by around 2% each year. Yet it is not included in most climate models and global change assessments.

The Cranfield team argues that it should now be considered alongside land-use and other climate drivers of carbon cycling.

Light pollution can be easily addressed, say experts

Importantly, unlike many other global climate stressors, light pollution is easily reversible.

"Unlike climate change, we could reduce light pollution almost overnight with better lighting design," said Dr. Johnston. "Adopting dimmable, directional, and spectrally sensitive lighting technologies is an immediate and achievable improvement."

"Since lighting accounts for around 15% of global electricity use, and growing evidence links excessive nighttime light to negative effects on human health, tackling light pollution represents a rare win–win–win for the environment, energy efficiency, and well-being."

The study leveraged the FLUXNET2015 network of carbon flux towers and global nighttime light datasets, enabling the detection of subtle, large-scale patterns linking light intensity to carbon exchange.

More information: Widespread influence of artificial light at night on ecosystem metabolism, Nature Climate Change (2025). DOI: 10.1038/s41558-025-02481-0.

Citation: Light pollution: The silent threat to the planet that's easily solved (2025, November 12) retrieved 12 November 2025 from <a href="https://phys.org/news/2025-11-pollution-silent-threat-planet-easily.html" rel="nofollow">https://phys.org/news/2025-11-pollution-silent-threat-planet-easily.html</a>

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

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the fake charity, the Photoshop predator, and other times AI got it wrong - Ask a Manager

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We recently talked about times AI got it really wrong, and here are 20 of the most ridiculous stories you shared.

1. The fake initiative

Our execs usually send out a hype email right before the annual employee morale survey, emphasizing wins from the past year, basically trying to put people in a positive frame of mind.

Last year’s included the announcement of a major new program we knew employees really wanted. But it was a bit surprising, because it fell in an area my team was responsible for, and we were out of the loop, despite advocating strenuously for this over the years. So I went to the exec to a) convey enthusiasm for his newfound dedication to launching this program and b) ask what support he needed from my team/get us involved again. It turned out the program wasn’t launching at all; he had just asked AI to edit the email to make it sound more exciting and appealing, and it had done so by … launching my initiative.

2. The predator

Sometimes at work my colleague uses AI in Photoshop to extend a background in a photo or clean up the background. We had a photo of a senior staff member outside: the background shows a building to the left of him and some trees and a road to the right, but it was portrait and we needed landscape. He asked Photoshop to extend the background on the right.

It generated a scary looking woman creeping up behind the staff member.

3. The nickname

I was on a Zoom call with AI notetaking software and was referring to a colleague named Bridget–but on the transcription, every time I specifically mentioned her name, it appeared as “Piglet.” This did not happen when others on the call said “Bridget”! It looked like that was just my nickname for her. I was so embarrassed.

4. The fake charity

My company hired an account manager who insisted he was a phenomenal writer and asked if he could contribute to our blog. The first pieces were just AI slop so I politely thanked him and said we had plenty of posts already.

So he posts a third “article” on his own LinkedIn account in which the AI described how our company collaborated with the CDC on researching a certain disease and publishing a groundbreaking study. Then we apparently went into underserved communities and funded a bunch of clinics and immunizations. NONE of this happened. It was hours before I saw it and forced him to take it down, and there were many surprised comments and shares. Months later, we were nominated for an award on our commitment to caring for vulnerable populations.

5. The transcript

I forgot the meeting was being transcribed and was talking to my cat while waiting for others to show up. “Baby, let me put it in” was at the top of the transcript to my absolute horror.

I was talking about his ear mite drops.

6. The grievance meetings

At my former workplace, the HR director did not know that her AI notes tool was recording her classified grievance meetings with the union representatives and sending a full recap after each one to all parties invited on the calendar invite, even if they weren’t in attendance. We got an email after a bit saying no one was allowed to use AI note takers any longer.

7. The “verifiable information”

Me: I’m doing a competitor analysis on [product type] for [customer segment]. Please give me an overview of all the [product type] products offered by banks in [my country] for this type of customer.

AI: (gushes) Sure! What a fantastic question, you’re a genius! (paraphrasing). Here is the overview.

Me: (searching for one of the product names listed … cannot find it anywhere) I can’t find this product anywhere. Did you make it up?

AI: Ooooh … did you mean actual products? Sorry! In future I’ll only reference verifiable information.

Me: (eye roll, crying into coffee mug, closes AI window)

(It continued to manufacture content.)

8. The job description

My mother is on the board of a wildlife habitat nonprofit. They work with wetland preservation and with both bats and owls. They were looking for a new director, so someone on the search committee decided to have AI make up the job listing. It included several useful traits (a reasonable amount of education, experience with fundraising, etc.) – but it also said the position required “five years’ experience teaching birds to fly.”

They rewrote the job listing.

9. The performance review

I had an employee request to use an AI to take notes during her performance review. The summary was one line: “No meaningful conversation took place”. I was glad I decided to take pen and paper notes because it was a very productive conversation indeed. Apparently the AI disagreed!

10. The baby announcement

At the end of a meeting, a colleague asked their boss to stay on the line for a couple of minutes. The colleague then confidentially shared the great news that they were expecting a baby, and they and their boss talked about a few next steps to plan for parental leave. The AI notetaker then sent out notes to everyone who had attended the meeting with the headline, “Colleague Is Having a Baby.”

11. “Dazzling you”

I’ve been involved in beta-testing and quality-controlling AI translation output because my employer wants to see if has utility in professional use cases. Here are some highlights:

– In an AI translation of a report about elder abuse, it randomly inserted the word “child” in front of the word “abuse” in various places. The concept of “child” did not appear in the source text at all.

– Every single abbreviation in the text was incorrect in a different way every single time. There was not a single correct abbreviation, and not a single abbreviation was translated the same way twice.

– The word “negro” was randomly inserted into a sentence for no apparent reason. This was early in my exposure to AI translation and I had no idea it could mess up that badly, so I spent ages trying to figure out if there was some stealth hidden racist dogwhistles in the source text. A colleague of mine also had a recurring problem of the word “bitch” randomly being inserted into sentences.

– Random misnegating – for example, the statement “more work is being done” is translated as “no more work is being done,”

– It translated the standard “Dear Sir or Madam” opening of a letter as “Dazzling you.”

– Rewording the source text in the source language rather than translating it. Yes, all the settings were configured correctly.

12. The Powerpoint

I asked Copilot to create a table comparing two things. It did an okay job. Then Copilot asked me if I wanted a Powerpoint slide of the table. I said sure, since I was going to put it into Powerpoint anyway. Copilot created the ugliest Powerpoint I have ever seen. Three slides (I only needed one) with a color scheme of lavender, salmon pink, and orange. The background of each slide had kind of a plaid pattern a coworker said reminded her of her grandmother’s couch. A random picture in a cartoon cloud shape.

However, that is better than our company’s internal AI. It doesn’t have the ability to output content into powerpoint, excel, etc, but it thinks it does. It’ll offer to create one for you and then do nothing. Coworkers have spent ages trying to figure out where AI is saving their non-existent files.

13. The comp titles

I work in publishing and I wanted to do some research on competing titles for a potential book we had in the pipeline. Asked AI for the bestselling current books on the topic, and it came up with a list that had some really interesting titles on it – great, I thought, I’ve never heard of half of these so we definitely need to check them out. Yep – turns out the AI had just completely made them up.

14. The editable document

Me: Copilot, can you turn this scanned PDF into an editable word document?

Copilot: Sure thing, Another Kristin, here you go!

Me (after opening the file): Copilot, this file is completely blank.

Copilot: Sorry, I made a mistake, here it is!

Me: (opens second file, sees that it is also blank, closes AI window and puts in request for OCR software)

15. The attack

A friend of mine showed me an AI summary of a meeting where the AI notetaker decided to attack someone for no reason– in the middle of the notes about what everyone was saying, it inserted, “Jane contributes nothing to the conversation.” I guess it was accurate because the coworker had been quiet since that part of the meeting wasn’t relevant to her projects … But why did it do that???

16. The scam

We work with a lot of small businesses just starting up, and as a result are asked to recommend professional services often. Knowing this, a client passed on a discreet warning about the bookkeeping firm we’d recommended to them. They had issues with their accounting software, Quickbooks, and called for help. It was right when Google started providing AI summaries for everything, and apparently their account rep pulled the phone number for Quickbooks’ support out of the AI summary, rather than off the website.

You can probably guess where this is going. The number wasn’t legit, but instead put him in contact with a scammer who’d managed astroturf their way into the AI summary. The account rep gave the scammer full access to our client’s accounting software before he realized his error. Our client didn’t share a lot of details about the damages — I got the sense that they were saying very little because they were planning legal action — but they wanted to let us know so we wouldn’t recommend them again.

17. The transcript, part 2

A woman I work with introduced herself before an online presentation. Her last name is Buckman. The AI transcriber recorded her introduction as “Hi, I’m Amelia. F*ck, man, it’s nice to see you all today.”

18. The transcript, part 3

Two people stayed on the call after the rest of the team had left and complained about others on the project. Not only did the transcription record this, it tagged the individuals being discussed in the summary as an action item: “@Jane needs to stop dragging her feet and get her sh*t together”

19. The equipment

I recently saw a ~$50,000 piece of industrial equipment damaged and taken out of commission for about a month because Google AI search told a worker that the tightening torque of a screw was 50 ft*lb instead of 50 in*lb.

This resulted in them over-tightening the screw by a factor of 12, which unfortunately didn’t strip the threaded hole (which would have been a smaller problem) but instead warped a bearing assembly that required a full rebuild at considerable difficulty and expense.

The kicker is that the correct torque value was clearly printed in the service manual that is stored in the machine.

20. The privacy expert

We once had a IT person come into a meeting to talk about the importance of data privacy and security who didn’t realize he had an AI notetaker signed in until someone pointed it out.

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