Dr Julia Shaw ✓

@drjuliashaw · London, England · joined 24 Sep 2015

Criminal psych & AI cognitive security. Visitor at @GovAIOrg, research @aiatkings. PhD in false memory. Bestselling author & award-winning sci comm

31 431Followers

2 742Following

9 563Posts total

26.2KViews on collected posts

Derniers posts

Dr Julia Shaw ✓@drjuliashaw4 Sep

Even if you have never shared personal information with an AI, it may still know how you think, and what you like through "inverse theory of mind". And your AI-gen persona is incredibly accurate, according to a new study. Through an "inverse theory of mind" pipeline, Mengyu ht

811 views · 3 likes · 1 reposts · 1 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw2 Sep

How do we safeguard human thinking from AI "manipulative dark patterns"? Can introducing a tool for "cognitive friction" help? A small new study (22 Aug) found that forcing people to be aware of dark tactics, or forcing them to think more about certain AI content, (aka: https://

1K views · 4 likes · 1 reposts · 1 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw1 Sep

In addition to a medical, and drug, history, should doctors be taking a "technological history" to help with diagnosis and treatment? A new paper (25 Aug) proposes that a "technological history" in clinical/medical settings could completely change the way that psychological htt

1K views · 3 likes · 0 reposts · 2 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw29 Aug

@drjuliashaw Huge problem with this paper…this statement is inaccurate... > selected as a controlled snapshot across model classes and laboratories When you run a hosted model like that, the model and (invisible) harness are constantly shifting behind the curtain, as is the co 36 views · 0 likes · 0 reposts · 0 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw28 Aug

As you interact longer with an AI, does it become more sycophantic... and more wrong? It seems so . As "AI systems acquire greater autonomy, sycophancy becomes compounding rather than merely persistent. Systems designed with human oversight loops may inadvertently create the h

6.4K views · 6 likes · 1 reposts · 1 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw28 Jul

@drjuliashaw #ScrapAI 34 views · 1 likes · 0 reposts · 0 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw28 Jul

@FLI_org Also, by "the" paper of the year I don't mean the only, but the most comprehensive! 583 views · 0 likes · 0 reposts · 1 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw28 Jul

I also like the term by @FLI_org, "epistemic virtue", which means AI presenting clear, calibrated answers without ulterior motives and supporting, rather than undermining, users’ ability to make sense of the world." https://t.co/UtaDbGWPTw 708 views · 1 likes · 0 reposts · 1 replies Open on X →

Dr Julia Shaw ✓@drjuliashaw28 Jul

AI epistemic risks has got to be one of the most interesting areas at the moment, and it highlights why epistemic *resilience* is so important. The paper of the year on this (and quite possibly the most important paper ever on this issue) highlights that these risks are https://

15.6K views · 78 likes · 27 reposts · 8 replies Open on X →

Face aux comptes de taille comparable

9 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. en dessous de ses pairs à la fois en portée et en engagement.

Vues médianes811ce compte955médiane pour 10K–100K

Portée, %2.58%ce compte3.52%médiane pour 10K–100K

Engagement, %0.48%ce compte1.56%médiane pour 10K–100K

Indicateur	Ce compte	Médiane pour 10K–100K	Rapport
Vues médianes par post	811	955	0.85×
Portée (vues ÷ abonnés)	2.58%	3.52%	0.73×
Taux d'engagement	0.48%	1.56%	0.31×

Autres comptes de cette tranche → Comparer avec un autre compte → Comment ces repères sont établis →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

15.6K28 Jul

708

583

6.4K28 Aug

3629 Aug

1K1 Sep

1K2 Sep

8114 Sep

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.72%28 Jul

0.28%

0.17%

2.94%

0.13%28 Aug

0.00%29 Aug

0.48%1 Sep

0.59%2 Sep

0.62%4 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.56%.

What the audience does

Likes41.7%96 in total

Reposts13.0%30 in total

Replies6.5%15 in total

Bookmarks38.7%89 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Derniers posts

Face aux comptes de taille comparable

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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