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EssaysConcerning | Essays, musings & missives – concerning science, art & society — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Artificial Intelligence →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
informatics-society.org ↗	66 match 1 shared topics	Informatics Society — Advancing Information Science Research	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
kayuripatel.com ↗	66 match 1 shared topics	Kayuri — Essays on Cognitive Science, AI & Behavioral Economics	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
edcults.com ↗	65 match 1 shared topics	EdCults - Data Science, AI & hands-on training	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
odins-ai.net ↗	65 match 1 shared topics	Musings on Artificial Intelligence - Musings on Artificial Intelligence	en	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none
shapethevision.com ↗	65 match 1 shared topics	shapethevision \| Data \| Strategies \| Business & Mission	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
icapai.org ↗	65 match 1 shared topics	2024 theme: Human-Centric AI for the Digital Society – Faculty of Computer Science, Engineering and Economics – Høgskolen i Østfold	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ejsays.com ↗	65 match 1 shared topics	EJ Says: AI, Ethics and Society	en	artificial-intelligence	robots llmsaihumans	emailphone	full · 12
crazydata.eu ↗	65 match 1 shared topics	CrazyData Europe - Data Science, Big Data, Artificial Intelligence, Cognitive Computing	European Union en	artificial-intelligence WordPress	robots llmsaihumans	emailphone	none
charlie-arsenec.com ↗	65 match 1 shared topics	Charles-André Arsenec \| Machine Learning & Data Science Projects	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
atauslu.com ↗	64 match 1 shared topics	Ata Uslu – Computer Scientist \| AI, Social Networks, Human Behavior	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
qut-aiml.org ↗	64 match 1 shared topics	QUT AI & ML Society	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
atsushi-datascience.com ↗	64 match 1 shared topics	Atsushi's AI &Data Science Hub	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ranjitsingh.me ↗	64 match 1 shared topics	Ranjit Singh – AI on the Ground, Data & Society	en	artificial-intelligence WordPress	robotsllmsaihumans	emailphone	none
ehabshanti.com ↗	64 match 1 shared topics	Ehab Shanti – Demystifying AI, Networks & Digital Society	en	artificial-intelligence WordPress WooCommerce	robotsllmsaihumans	emailphone	none
shamimkheirani.com ↗	64 match 1 shared topics	Shamim Kheirani \| Graduate Researcher in Cognitive Science, HCI, and AI	Italy~ en	artificial-intelligence	robotsllmsaihumans	emailphone	none
rachelchiong.com ↗	64 match 1 shared topics	Rachel’s Blog \| This is Rachel’s blog - containing learnings from ELEC4630 - Computer Vision and Deep Learning	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
ranu.io ↗	64 match 1 shared topics	Ranadheer Malla - Social Data Scientist	en	artificial-intelligence	robotsllmsaihumans	emailphone	none
industrialdatascience.org ↗	64 match 1 shared topics	IDS 2020 - Industrial Data Science Conference	en	artificial-intelligence	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.