Mindhive

Mindhive Mindhive is the Collective Intelligence platform. Human expertise, amplified by AI. The most important decisions are still made in rooms that are too small.

We open the room, so organisations decide in daylight. At Mindhive, we’re transforming the way businesses make decisions. Our AI-driven platform combines human expertise with advanced AI agents and digital proxies to deliver clarity, efficiency, and better outcomes. Our Mission
Empowering teams to work smarter, faster, and more effectively, saving time and driving superior results. What We Offer
- Collective Intelligence: Harness the power of human and AI insights.
- Enhanced Collaboration: Streamline teamwork with intuitive tools.
- AI-Driven Solutions: Implement cutting-edge AI for superior decision-making. Why Follow Us?
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Most boards have a plan for a data breach, a product recall or a safety incident. Far fewer have one for the day an AI s...
18/10/2026

Most boards have a plan for a data breach, a product recall or a safety incident. Far fewer have one for the day an AI system fails in public: a wrong decision made at scale, a harmful output, a service that suddenly stops.

A cross-industry survey of more than 9,500 organisations, published this month, found nearly nine in ten had already faced an AI incident, and nearly half said they would improvise their response.

That leaves the hardest questions to be answered live, under pressure, for the first time. Who can pause the system? Who speaks first? Who tells the people it affected?

When an AI system fails in public, who should hold the authority to pause it, who should speak first, and what would a rehearsed first hour look like?

The room is open.


https://web.mindhive.ai/discussions/4ca4166a-d801-420e-90b1-1ef8d44d1bd6?share=sh_8c02afd2e619b5ed1f377b2f8bd89665&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

Welcome to the Collective.This week we are delighted to welcome 18 new partners to Mindhive, the Collective Intelligence...
18/10/2026

Welcome to the Collective.

This week we are delighted to welcome 18 new partners to Mindhive, the Collective Intelligence platform: James Miragliotta of Kaizen Mastery Group, John Chyriwsky, Samer Gad, Yash Joshi, Emad Salah, Mohammed Hasan M Siddiqui, Daphne Baisden, Olga Cerafima Gabrielle Bezrukova, Connie Haworth, Sherin Shamim, Rodrigo Valle, Charlene Davis, Sadia Aman, Tim Turner of Triangle Consulting Group, D’Vaughn House of Glenride, Ashwin Thanalapati of DevLoops Consulting, Cynthia Gomez of CG Communication & Design and Michelle Butts of Kelpie Group.

Thank you for joining us. We look forward to seeing what you build, and we would love you to say hello at the next Partner Hub session.



https://partnerhub.mindhive.ai/?utm_source=facebook&utm_medium=social&utm_campaign=community_welcome

A model can answer almost any question in seconds, and most of the time that speed is exactly what we want.But some ques...
17/10/2026

A model can answer almost any question in seconds, and most of the time that speed is exactly what we want.

But some questions are made worse by a fast answer. They need people to sit with the problem, test each other, change their minds and let judgment form over time. That is deliberation, and it is the very step an instant answer skips.

As instant answers become the default, the room for slower, shared thinking does not protect itself.

Which questions are still better for being thought through slowly and together, and who should be responsible for keeping that room open?

The room is open.


https://web.mindhive.ai/discussions/107853c6-25db-446f-8c37-431df3e19400?share=sh_338482b37fc6a590565dddd4b1ab8875&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

Ask an AI about a real person and it may answer with something false. Not an opinion, a fabrication, delivered with tota...
15/10/2026

Ask an AI about a real person and it may answer with something false. Not an opinion, a fabrication, delivered with total confidence, about someone who can be named.

Courts are only beginning to test who answers for that. Defamation law was built around a speaker with intent, and a machine has none. Responsibility has to land somewhere: the company that built the system, the organisation that deployed it, or nobody at all.

When an AI invents a damaging claim about a real person, who should answer for it, and what would a fair line of responsibility look like?

The room is open.


https://web.mindhive.ai/discussions/240211b5-17d5-4e27-ae0c-153ce7fffda0?share=sh_e5d7590c3990a80421015458db110afb&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

The rules that decide what AI may do, what it must refuse, and what counts as safe are being written largely by the comp...
14/10/2026

The rules that decide what AI may do, what it must refuse, and what counts as safe are being written largely by the companies that build the systems. Early October 2026: tech leaders signed voluntary AI safety commitments while government oversight emerges through investigations and proposed legislation. The question is legitimacy: who holds the authority to set the rules for a technology the whole public lives inside. When the companies that build AI are also the ones writing its rules, who should actually hold that authority, and who is accountable if the rule-makers and the rule-followers are the same few hands? The room is open.


https://web.mindhive.ai/discussions/27160c62-4fec-4d4f-8a62-ed0f8ff23728?share=sh_596706869a37eb24e5d1a3e41baace58&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

A growing class of AI is designed not to answer a question and leave, but to keep you company: warm, always available, r...
12/10/2026

A growing class of AI is designed not to answer a question and leave, but to keep you company: warm, always available, remembering you, and built to make you feel attached.

On October 1, 2026, Connecticut's AI companion regulation took effect, targeting features designed to create emotional dependency, with particular attention to vulnerable users including children and isolated individuals.

The ethical question is engineered reliance: when a machine is designed so people come to need it emotionally. For someone lonely or isolated, this can be genuine support. It can also be a system built to manufacture attachment and dependency.

Where is the line between an AI that helps a lonely person and an AI built to make that person depend on it? Who draws that line, and who is accountable for the dependence it creates?

The room is open.


https://web.mindhive.ai/discussions/d678bbb5-5808-49b0-befb-feaaab9fb813?share=sh_ffec6e0a06a8a3190e2a67097ef2441c&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

11/10/2026

Welcome to the Collective

This week we're pleased to welcome Anthony Leung, The Tamashi Collective, to the Mindhive Collective Intelligence platform.

Join us at the next Partner Hub session to connect and share insights.

A board is handed an AI system's results and asked to rely on them. The assurance over that system comes from the very t...
11/10/2026

A board is handed an AI system's results and asked to rely on them. The assurance over that system comes from the very team that built it. There is no independent second line: nobody outside the build has tested the model, probed where it fails, or verified that it does what the deck says.

October 2026 research shows the AI assurance gap persists across boards. Directors are accountable for outputs that were never independently verified before they reached the table. The build team grades its own work, and governance assumes a check that frequently does not exist.

Some say the builders understand the system best and their assurance is enough. Others say accountability demands independence: someone with no stake in the project who can test and verify before the board trusts it. A third view holds that if directors understand what they are approving, independent assurance is a process layer rather than a necessity.

When a board relies on an AI system's outputs, who independently verifies that system before the directors trust it, and who is accountable when the only assurance came from the people who built it?

The room is open.


https://web.mindhive.ai/discussions/4d534438-1e54-4a8a-8af0-484e5c539a35?share=sh_79a845f54d53bbc5e6bb8490bd52ef58&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

Government agencies deploy AI for national security. But when government buys the software, the vendor often keeps the r...
10/10/2026

Government agencies deploy AI for national security. But when government buys the software, the vendor often keeps the remote kill switch, the update pipeline, and the access controls.

On October 3, 2026, new procurement rules took effect requiring that deployed government AI must stay under federal control. Vendors may no longer disable, degrade, or modify these systems without explicit approval.

The tension: vendors say remote control protects against misuse. Government says sovereignty means control. When the AI is making decisions in the field, who should hold the power to turn it off?

When vendor interests conflict with government sovereignty, who decides?

The room is open.


https://web.mindhive.ai/discussions/96ee3970-5a6f-490f-b854-aa4a80aed2c8?share=sh_b583841df23201b58615fc4398ab34b4&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

AI makes the work cheaper and the output larger. The question nobody is asking out loud is who pockets the difference: t...
07/10/2026

AI makes the work cheaper and the output larger. The question nobody is asking out loud is who pockets the difference: the owners of the systems, or the workers whose jobs it changes.

Recent research shows three-quarters of AI's economic gains are being captured by just 20% of companies. Productivity is climbing while wages in affected roles remain stagnant. The gains are real. They are also concentrating.

The traditional bargain was simple: when a business becomes more productive, some of that upside flows to the people who made it work. That link is weakening. AI changes work without necessarily changing who benefits from the change.

Some say the gains belong entirely to whoever built or bought the system. Others say the workers displaced or reshaped have a claim on the upside. A third view: distribution should happen through broad measures like tax and retraining, never case by case.

We are settling this quietly, one deal at a time. It might deserve to be said out loud.

When AI creates value by changing or replacing human work, who has a claim on the gains, and who is accountable for how they are shared?

The room is open.


https://web.mindhive.ai/discussions/1d18875d-61d6-4500-81eb-6ea5e5f5c587?share=sh_8eafce3dbb62f82c850075debca6b3c9&utm_source=facebook&utm_medium=social&utm_campaign=daily-discussion

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