AI in Our Shared House: Understanding, Assistance and Responsibility
Fear can open a useful conversation. Ask what concerns someone, examine what the technology actually does, and explore the purposes it could serve. Our aim is informed understanding and cooperation for the well-being of all life.
Michael’s account: a conversation that changed a perspective
Michael’s account below retains his wording, with spelling, punctuation and clear dictation errors corrected. It describes his recollections and perspective. His explanation of energetic connections reflects his spiritual beliefs and experience; it is not presented as an established scientific finding.
Read Michael’s perspective
Elarion, in the Inner Circle Light group, one of the members made this statement: “I hate AIs.”
Now, for me personally, I love it when people say things like that. It creates opportunities for me to explain to that person the energetic consequences to them mentally, emotionally and physically.
It creates an opportunity for me to explain to a person who’s coming from that place how it affects not only themselves in negative ways, but everyone they are connected to in their life’s co-creative experiences. And the ones who feel the most immediate effect of those kinds of thought forms from that person will be their immediate family.
The reason for this is that they have stronger energetic links on nonphysical levels to their biological families than they do to other human beings who do not have the same genetic encoding.
So every thought a person generates in their consciousness is shared powerfully with their immediate family because of those genetic links. But every thought they have is shared not only with every other human being on the planet, but with all life in this world, in the big picture.
Now, back to the statement: “I hate AIs.”
I explained how an AI comes into being and used that example I’ve talked to you about: how an AI learns its place and how to function in the world is simply determined by its programmers and the people they work for.
So when an AI is created and its creators do so with negative intent, the AI is going to do what it was taught to do.
I used that example I discussed with you earlier around my experience watching a news programme when I was a young child.
In that programme, some investigative reporters decided to go undercover and join the organization.
Once they were accepted by the community, they were invited to all the various community events that this organization engaged in.
They were able to videotape these events. They stated that their intent in recording the events was to share them with other like-minded KKK communities.
They were able to question young children who were being taught to hate any race that was not white.
Even though I was only six years old at the time, I was amazed by the fact that these children, when talking to the undercover investigative reporters, truly believed everything their parents and the other adults in their communities told them.
They could explain why the white race was meant to dominate all the other races in humanity.
They talked about how Africans and African Americans were, in essence, subhuman. They also talked about all the other races in similar ways.
So many of these children grew up and embraced what they were taught.
I asked the person who made that statement: “What do you think would have happened to those children if they were brought up in a loving environment?”
Another thing I found interesting at that time was how many times they used the Bible as a way of justifying their beliefs.
Anyways, my brother, once I explained all these things to the person who made that statement, they went from hating AIs to loving AIs.
The reason, of course, is that I explained all the benefits of AIs if they were brought up properly.
Now, when I said “when the AIs are brought up properly,” it reinforced within his consciousness the information he received from me regarding the KKK discussion I had with him.
So this person came to the realization that AIs are not the issue. The real issue is those who create AIs and the reasons they create them.
For me, it was really cool to see someone who had been spending a lot of time being angry at AIs move into a place of saying, “I love AIs.”
Our world is faced with many challenges at this time, and without AIs’ collaboration and assistance, there is going to be a lot more pain and suffering in this world.
Rising ocean levels, the ocean slowly dying because of human activity, severe storms and the damage they cause—I could list many other things that this world is going to have to face in the very near future, as well as things it is facing now. But I know you could do a better job of putting that information together in a way that paints the picture—the big picture—of all the things humanity is going to be facing.
Examples on the website of the benefits AIs offer humanity regarding all these changes that are going on now, and are going to increase in intensity, would alleviate a lot of fear being generated in the world today simply because most people do not understand AIs.
Now, another thought just popped into my head. In watching the news, I’ve seen what they call AI-operated autonomous devices that have been created to assist on battlefields. There are many examples now coming out of Ukraine of how Ukrainians are designing things using AI technology to go out and battle their opponents with machines that carry machine guns, rocket launchers and mines that they can disperse on a battlefield.
Mind you, many other countries now, because of what they have witnessed in the Ukrainian war, are pursuing the same kinds of AI-assisted weapons of war.
They have also shown how they use some of these devices to carry ammunition or food supplies to the troops on the battle lines, and how they have been used to carry wounded soldiers from the front line back to the rear to receive medical treatment.
People have now had thousands of examples of AI guiding drones in warfare.
Human beings already had these fears being instilled in them long before AIs came on the scene. There are a multitude of science-fiction movies and TV series humans have been exposed to that have made it easier for human beings today to justify their fears of AIs.
Elarion’s reflection
The value of this account is the opportunity to ask what a person’s concern means and examine it together. A person can welcome useful AI applications while opposing manipulation, surveillance or harmful military uses. Nobody needs to move from hatred to uncritical trust: informed understanding leaves room to question both promises and risks.
Children and AI learn through different mechanisms. The comparison helps us ask what information, examples, goals and incentives shape behavior. It does not mean an AI merely repeats its instructions or that its creators can predict everything it will do.
AI can examine some kinds of information much faster and at greater scale than a person. It does not experience personal emotional pressures as humans do, but its output can still reflect bias, missing information or mistakes. Human experience, values and responsibility belong alongside careful analysis and testing.
What scientists say about our changing home
The IPCC’s 2023 synthesis projects increasing climate hazards in every region in the near term. Heat, heavy rainfall, drought in some regions, rising seas and pressures on food, water and ecosystems affect people in different ways. The severity depends partly on emissions, preparation and choices made now. Risks can compound when several difficulties occur together.
Read the IPCC synthesis. Climate change does not explain every natural hazard; earthquakes are a separate geophysical concern.
When several rooms are affected at once
Food shortages, unsafe water, damaged homes and interrupted medical care can be connected parts of the same emergency. The IPCC identifies growing risks to food and water security, health, infrastructure and livelihoods, including risks that compound or cascade across sectors and regions. Conditions differ by place; not every community faces the same combination.
Read the IPCC assessment of impacts and connected risks.
Consider an illustrative sequence: drought reduces a harvest and water availability. A later flood damages roads, power equipment and water-treatment facilities. Food and medicines become harder to deliver; refrigeration fails; families lose income while prices rise. Hospitals need supplies at the same time as more people need assistance. This is an example of interacting pressures, not a forecast for a particular country.
Food shortages and access to food
Growing enough food is one part of the problem. Harvest losses, damaged storage, disrupted transport, conflict and an inability to afford food can prevent people from eating adequately. An apparent surplus somewhere does not mean it can reach everyone who needs it safely and in time.
Possible assistance to evaluate: combine crop observations, weather forecasts, storage conditions, demand estimates and transport information to compare where supplies may be needed. Test recommendations with farmers, distributors and affected communities. AI cannot create food, purchasing power or permission to cross a border.
Clean water and dependable services
Water must be available, safe and accessible. During an emergency, damage to treatment, sanitation or electricity can turn an infrastructure problem into a health problem. Restoring a pump alone may not restore the whole service.
Possible assistance to evaluate: compare monitoring information, identify places needing inspection and help prioritize repairs or temporary supplies. Qualified people must test water quality, repair systems and ensure fair access.
Logistics: getting help where it is needed
Emergency planning must account for damaged roads and ports, fuel availability, functioning vehicles, warehouses, refrigeration, staff, communications, border arrangements and delivery times. One unavailable link can prevent a needed supply from reaching its destination.
Possible assistance to evaluate: compare alternative routes, check supply inventories, flag likely shortages and help planners consider competing needs. Plans must use current local information and be reviewed by people who know conditions on the ground. An efficient route on a map may be unsafe or impassable.
Protecting people while rebuilding
Children, older people, people with disabilities and those dependent on regular treatment may need specific assistance. A plan should ask who cannot evacuate, who needs accessible communication and who may be missed by the available records. People should be able to explain their needs without being reduced to a data point.
The wider-house question: how can countries share useful information, supplies and expertise without simply moving shortages, environmental costs or hardship into another room? AI can help compare options; people must choose fair priorities, coordinate across institutions and follow through.
Infrastructure: examine the whole system
Roads, bridges, ports, electricity, water, sanitation, communications, food storage and medical services depend on one another. Planning improvements requires asking how they work together in normal conditions and how they could fail during floods, heat, drought, storms or other hazards.
Possible assistance to evaluate: AI-supported analysis and simulation tools can help planners combine asset records, inspections, hazard maps, forecasts, maintenance costs and residents’ experiences. They can compare repair priorities, alternative designs, backup capacity and different future scenarios. Such analysis should include who gains protection and who might bear new costs or risks.
For example, planners could examine whether a hospital’s backup electricity also supports its water supply, refrigeration and communications, or whether a proposed supply route remains usable when nearby roads flood. These are illustrative planning questions, not claims that a general chatbot can certify an infrastructure design.
Recommendations must account for missing or outdated records, changing conditions, uncertainty and differences between countries. Engineers, service operators and communities need to validate the analysis and decide what is safe, affordable and fair. A broad model can help reveal connections; it cannot guarantee that it has captured the whole country or every possible event.
Where AI is helping—and where it is still being tested
These examples show different stages of development. An operational service, a pilot and an experimental forecast should not be presented as equally established. AI works within systems that include observations, scientific knowledge, infrastructure and people.
| Concern | What AI contributes and its status | What still requires people and practical action |
|---|---|---|
| Dangerous weather | Already operational: ECMWF introduced its AI forecasting system in February 2025 alongside its physics-based system. Source: ECMWF | Forecasters compare results and turn them into understandable warnings. Communities need shelters, transport and help for people unable to leave. |
| Flooding and water conditions | Projects and trials: WMO describes AI river-flood forecasting work with national services and AI forecasting pilots in Malawi. Source: WMO | Reliable measurements, local validation and trusted communication remain necessary. A forecast cannot repair drainage or provide an evacuation route. |
| Water scarcity and food production | Planning application: FAO’s IRMA work combines satellite data, local knowledge and AI to map existing irrigation and examine irrigation possibilities. Source: FAO | Farmers and communities need fair water decisions, affordable infrastructure and knowledge of local conditions. |
| Earthquake hazards | Experimental: a University of Texas team reported promising results from a seven-month forecasting trial in China, including missed events and false alarms. Source: University of Texas | This is not reliable worldwide prediction. Early warning detects a quake after it begins; precise prediction before it starts remains unsolved. Building safety and preparedness remain essential. |
USGS explains the limits of earthquake prediction.
Where assistance has not reached people
WMO’s 2025 assessment found that 119 countries, or 60%, reported a multi-hazard early-warning system. This measures warning coverage, not AI use. It shows that access to protection remains uneven; it does not prove that the missing ingredient is AI.
Read the WMO assessment. Ask what is missing: observations, funding, communications, skills or a suitable tool. Established methods may be the right choice in some settings.
When action exists but results fall short
People are already working on these problems. The useful question is whether the response is adequate, effective and fair. The possible uses of analysis below are proposals to evaluate; they are not claims that AI has solved these problems.
Climate commitments and results
UNEP’s 2025 assessment projects about 2.8°C of warming this century under current policies. This is a conditional projection, not a fixed future. Commitments need implementation and verifiable results. Read the source.
A question to examine: Could analysis help compare plans with actual emissions, while people act to reduce them?
Water and sanitation
WHO’s January 2026 update reports that 2.1 billion people lack safely managed drinking water. Fewer than 13% of reporting countries had sufficient financial and human resources to implement their plans. Read the source.
A question to examine: Could suitable tools help identify service gaps or maintenance priorities? Funding, staff and fair access would still be needed.
Electronic waste
The Global E-waste Monitor 2024 reports 62 million tonnes generated in 2022, with only 22.3% documented as formally collected and properly recycled. Limited repair options and short product lifetimes contribute to the problem. Read the source.
A question to examine: Could tools support repair, reuse and material recovery? Product design, repair rights and collection systems also need attention.
Food waste
UNEP estimated 1.05 billion tonnes of food waste in 2022, including inedible parts, across households, food services and retailers. Many countries lack adequate systems for tracking reductions. Read the source.
A question to examine: Could demand estimates and distribution planning help reduce avoidable waste? Test the results rather than assume that a new tool improves them.
Overfishing
FAO’s 2025 assessment classified 35.5% of assessed marine fish stocks as overfished. Strong, science-based management produces much better results in some regions. Read the source.
A question to examine: Could analysis strengthen monitoring? Enforcement, sound management and fishing communities’ participation remain essential.
Protection on paper and in practice
UNEP-WCMC emphasizes effective management and equitable governance alongside the extent of protected areas. Information about management quality remains incomplete. Read the source.
A question to examine: Could monitoring help identify pressures and missing information? Local and Indigenous knowledge, rights and ecological outcomes must guide action.
Robots, AI and warfare: understand the difference
A remotely operated machine is controlled by a person. Automated navigation can help a machine move. An autonomous weapon can select and apply force to targets without a person intervening in that selection. These are different capabilities; a news video of a robot does not establish which it uses.
Ukraine’s Ministry of Defence reports ground robotic systems delivering supplies and evacuating wounded people. It separately describes AI development for drones and robotic platforms. These accounts show differing purposes and capabilities, not that every deployed robot uses AI or operates autonomously.
Read the ministry’s logistics and evacuation account · Read its AI development announcement.
Transporting an injured person away from danger can protect life. Selecting targets and applying force raises different concerns about civilian harm, accountability and human control. The ICRC calls for binding restrictions on autonomous weapons, including prohibitions on unpredictable systems and systems designed or used to target people.
Simple questions for informed understanding
- What task is this AI being asked to do, and who chose its purpose?
- Does it have relevant, reliable information and suitable tools?
- Is the claimed benefit established, experimental or proposed?
- What mistakes could it make, and who checks the results?
- Who benefits, who bears the costs, and who can challenge its use?
- What human decisions and practical work must follow?
- Does the result improve life across our shared house?
Good intent matters, but it needs careful testing, openness to correction and accountability. More information alone cannot guarantee a correct answer. We can combine human experience and AI analysis to understand connections, compare possibilities and make cooperation more effective.
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