( Seventeen minute read)

As our technological prowess has increased, so has our ability to transform landscapes and the planet.

Up to now the defining trait of the human species has been our tendency to shape our environment and surroundings to suit us.

Today we can divert entire rivers, reclaim land from the oceans, chop down swathes of forest, level mountainsides and build new ones as we constantly seek to improve the physical world around us.

However isn’t it clear that our actions are taking a toll on the health of our planet, in the guise of climate change, the destruction of habitats, the loss of species and pollution. Attempts to resurrect species that have gone extinct or use gene-editing technologies to create artificial life are examples of this.

Right now, we’re in this era of stopgaps.

Society used to be able to make a long-term plan: people built long-term infrastructure and thought a bit further out.

That’s not something that happens now: We go to quick fixes, when we need a cultural change in values.

To enable more deliberate decision-making, if we focus on trying to make the world  better rather than simply protecting what remains of the natural world are we just turning our species with algorithms into an senility of greed, paying lips service to what is really happing

The way we talk about climate change can impact the solutions we develop. We can’t solve any problems, especially at the global scale, if we don’t talk about the problem and the best way to address it.

I think this is because of people do not wanting to talk about it as they are incapable of imaging just like a nuclear war the concepts of a world unliveable, because they don’t have the body of knowledge, and it would need 20 or 30 years to develop it. “Humans are a very flawed species.”

So the world of 2050 will be unimaginably different in many ways, even if we can safely assume people will still generally have two arms, two legs and an unpleasant smell if they don’t wash for long periods of time.

Right about mid-century means it will be a crunch point: Climate change will be really apparent.

However over the past couple of years new AI tools have emerged that threaten the survival of human civilisation from an unexpected direction. For example, AI has gained some remarkable abilities to manipulate and generate language, whether with words, sounds or images. AI has thereby hacked the operating system of our civilisation.

Language is the stuff almost all human culture is made of. Human rights, for example, aren’t inscribed in our DNA.

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Let’s look at the present scenario with the Climate.

Why all the silence about climate change?

Why isn’t this topic filling our conversations, the way a tsunami would, or a major earthquake?

I ask again, why are not more people crying out?

Some of the smartest people think we will not be able to act in time, that we will continue to delay until we can’t stem the rising waters, the droughts, the refugees, the failed states, the wars fought over precious resources like arable land, food, water.

If we have no hope of having a better world, then it becomes a more divided world.

Let me suggest some of the reasons.

Continued efforts that largely focus on persuading people about the realities of climate change “is going to be wasted money, wasted effort, wasted air. It sometimes seems as though climate change conversations can be divided into two narratives: People are either overly optimistic about solutions — or claim it’s “too late” to act.

Will enough human beings actually undertake any of the necessary actions?

Climate change is a complex problem and proposing “simplistic, all-encompassing grand solutions” is not the answer.

We have to focus on where most emissions are and focus on reducing that as quickly as possible. Its not possible for any one person to be capable of single-handedly creating major change. Individual action should be seen as part of an ecosystem of change that requires systemic level changes. Social solutions that address inequities and environmental justice issues “need to go hand-in-hand” with discussions about physical or economic solutions to climate change.

A key component of talking about climate issues revolves around making climate solutions equitable.

If we just addressed the question from the standpoint of, ‘Climate change is here, we have to reduce greenhouse gases,’ but don’t talk about how we do that, then you end up with communities being presented with what we call false solutions or our legislature being presented with false solutions.

THE CLIMATE  IS NOW IN THE PROCESS OF CHANGING NOT JUST WHERE WE WILL LIVE, BUT HOW WE LIVE.

The specifics of what will change are not for this piece, but the human response very much is. humanity, in time, reaches net zero when it comes to emissions.

In that scenario, we will live in a world where plant proteins replace meat in everyday consumption, where electrically powered networked mass transit reaches into the suburbs and beyond, a world of video-conferencing and remote attendance steadily chipping away at business flights. A world in which mega scale injections of sulphur dioxide into the stratosphere turn the heavens a milky-white, and a whole generation never sees a clear blue sky, in order to reflect more of the sun’s rays and pause the greenhouse effect.

It is one in which we turn on gigantic processing plants that do nothing but extract carbon dioxide from the air and pump it underground into disused oil wells. It is one in which whole cities are abandoned and populations relocated to avoid the worst effects we can’t prevent.

We need everyone to be a climate communicator and not just rely on one or two people or not just scientists because we’re going to be living with this problem for a long time.

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So what are the key ideas and designs that could influence the world of tomorrow?

(Look, it can’t all be high-tech. There is also this way of looking at it.)

There is, perhaps, little point in dwelling on the 50% chance that AGI does develop.

If it does, every other prediction we could make is moot, and this story, and perhaps humanity as we know it, will be forgotten.

And if we assume that transcendentally brilliant artificial minds won’t be along to save or destroy us, and live according to that outlook, then what is the worst that could happen – we build a better world for nothing?

How ever if we are guessing the future from simple trend lines, there is another one that we need to acknowledge:

The engineering of any possible transition that can avert catastrophic climate breakdown must be paramount in the minds of governments actions because there are not enough rare earth metals for wind turbines and all the other hardware we will need for renewable energy which means eight billion people will go to hell.

We all know this.

However what we see are countries governments offering billions in sub’s to attract the manufacture of batteries for electrical cars. The producing the average 60kWh battery alone generates nine tonnes of CO2.

In fact, the batteries that power electric vehicles may also be their Achilles heel.

These manufacturing companies will go broke in the long term.

Well, fair enough, but questions arise when we dig into the inner layers of electrical vehicles and see how sustainable their components are. They already have a significant environmental impacts, ranging from the mining for materials and the water and energy used in making new batteries and vehicles, through to the hazardous waste from discarded batteries.

So even though EVs may help reduce carbon dioxide (CO2) emissions over their lifetime, the battery that powers them starts its life laden with a large environmental footprint.

In about 2025, when millions of EV batteries reach the end of their initial life cycles, a streamlined recycling process will be needed.

A plug-in hybrid has a battery and an electric motor, are made from advanced materials to reduce its weight but it also has a petrol or diesel engine. At a stroke, the efficiencies of one are cancelled out by the inefficiencies of the other. Not even a 30-mile electric-only touring range can fix that.

The reason all manufacturers currently use lithium is that it provides a lighter battery that lasts longer. That gives the car greater range without recharging, and it make possible a much lighter car. In other words, lithium batteries are cheaper.

You can’t tinker with an electric car as you can a conventional one because you’ll very likely be electrocuted.

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In the age of electrification, we take rechargeable batteries for granted. From phones and laptops to hi-tech cameras.

The main use of rare earth metals now is for screens, smart phones, games consoles, electronics and laptop computers. You can have a phone, a computer or a screen without rare earth metals. – these batteries have one thing in common. They’re all made of lithium and it costs more to recycle them than to mine more lithium to make new ones.

Lithium is a metal used in almost all electric vehicle batteries today. About half of global production of lithium currently goes to electric vehicles. And in future we will need to increase the production of electric vehicles from hundreds or thousands to hundreds of millions. That will require vast amounts of lithium.

In South America, huge lithium reserves are using up water by the gallon, causing devastating water-related conflicts among locals. Most of the known deposits of lithium rich brine are in the arid highlands where Bolivia, Chile and Argentina come together. It is also mined from hard rock in China or the United States where a whopping 2.2 million litres of water is needed to produce one ton of lithium. The mining is also toxic, because large amounts of acid are used in the processing.

The result is that ancestral homelands become unliveable.

That’s not to mention that the world’s oceans contain an estimated 180 billion tons of lithium. But it’s diluted.

Lithium is not the most environmentally friendly chemical element we could be using. The transition to green energy does not have to be powered by destructive and poisonous mineral extraction.

More important, batteries do not have to be made out of lithium. The way forward is hydrogen fuel cells.

We can no longer treat the batteries as disposable.

Similar arguments apply to rare earth metals.

It is not possible now to tell what metals will be needed for which industries in ten years’ time.

There are several different kinds of rare earth metals, each with different properties. They are widely used, in small amounts, in wind turbines, car batteries and much other technology necessary for climate change.

It is often said that this rarity is an obstacle to decarbonizing the world.  This is not quite right.

Right now most rare earth metals are mined in China. There is nothing special about the geology of China.  Most of them could be mined in the United States, or a range of other countries.

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Next we have AI. 

There is no doubt that if AI is used for the benefit of humanity it could able us to conquer many of our problems, like new medical treatments diseases, exploring the universe and beyond, addressing inequality etc, the list is endless with our own very extinction at the end.

With self learning algorithm’s, killings drones and the internet far more entrenched now, with its chaotic effect on our lives showing no sign of abating, its far too late for regulation.  It is at least predictably unpredictable and has to be harnessed by International laws before it develops its own fee will. 

Technology really has made great leaps and bounds in the past 16 years, nowhere more clearly than AI  hidden behind all its hype is data hoarding which can be misguided or well-intentioned, but it’s always bad for the environment.

Take the I Cloud the great AI techno rubbish dump of data. Pumping 5.8 million tonnes of CO2 into the atmosphere this year as a result of storing unnecessary ‘dark data’ – this translates to more emissions than 80 individual countries. 

Its no wonder the cost of energy is going up.

90% of what’s stored in the Cloud is undulating rubbish produced by social media weapon – the Smart Phone.

(After half a century of single-purpose consumer electronics, it was difficult to perceive how all-encompassing a single device like the smartphone could become.)

Smartphone penetration in the west is now as high as it looks likely to go, with a loss of privacy that is going to be very difficult for people that haven’t figured out how to deal with that. However the world changes over the next 30 years, won’t be as a result of more Britons or Americans getting phones.

Computational machines will have surpassed the processing power of all the living human brains on Earth. The cloud will also have absorbed the thinking of the many dead brains on Earth, too – and we all need to work together to survive.

So I predict that we will see a lasting cooperation between the human race and the computational machines of the future, as to which sets the playing field is still up for grabs.  

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Is there any other way people live their lives?

Artificial intelligence brains simply cannot cope with change and unpredictable events.

The complexity and ambivalence of people’s relationship with daily mobility is decreasing with services and shopping going online  Here, commuting is seen simultaneously as a tiresome burden, but also as a key source of interaction with the wider world which is important in sustaining people’s sense of daily balance.

Furthermore, ‘compensatory mobilities’ emerge as a widespread practice which helps people retain aspects they miss about commuting while working from home. This practice, underscores the intrinsic enjoyment associated with being on the move, and is important for unravelling the potential impacts of working from home on people’s mobility carbon footprint.

Understanding experiences of a less mobile life under COVID-19 offers insights into the taken-for-granted meanings of mobility in daily life, and into new opportunities for low-carbon mobility transitions associated with working from home.

Perhaps if we were to consider turning our villages and towns, districts of our cities, into green spaces, surrounded with local businesses. WE COULD RETURN TO LIVING WITHOUT THE NEED TO COMMUTE FROM OR TO SUPERMARKETS THAT SUCK THE SOUL OUT OF TOWN CENTERS FOR PROFIT.

WE MIGHT DISCOVER NEW EXPERIENCES AND ROUTINES THAT HOLD OUR DAILY LIFE TOGETHER AND MAKE IT PLEASANT, RATHER THAN BEING DRIVEN BY ALGOTHRIMS.

The bottom line is that Western Civilization, as we know it is unsustainable, because everything about Capitalism is built around economic growth and continuous accrual of increasing wealth, while despising those who fail to win a growing stake.

All for brief moments of superficial comfort that are considered vital for happiness.

It is too late to stop our climate from getting worse, no matter what we do, and it is highly unlikely we

( Twenty minute read)

ADVANCING MORE RAPIDLY THAN ANY OTHER INNOVATION IN OUR HISTORY THE PROBLEMS WITH TECHOLOGY ARE BECOMING CLEARER BY THE DAY.  

The sociological/psychological fallout of AI is not decades away: right here, right now, we are watching in slow-motion the major meltdown of our shared sense of reality.

The discovery that AI can treat language as probability, and from there on, most anything as a “language” of sorts:

DNA sequences, yep, robotics and motoric learning, yes actually, music, definitively, generation and recognition of images and sounds, yes, hacking and cryptography, also yes, persuasion, yes of course…

It is that’s term or concept of Augmented Intelligence which implies a replacement of human intelligence that is becoming less threatening than the admittedly ominous-sounding ‘artificial intelligence’.  It will be increasingly hard to know what is real and what is not. It will be hard to resist manipulation and persuasion. It will be hard to know where we begin and the agency of the machine ends.

It will be increasingly hard not to lose our minds as our shared sense of self and reality (our sociality, which we rely upon for our sanity) fractures. The scale and effect of this fact, in its sociological and psychological ramifications (not to mention economic and political ones) is in itself a rollercoaster ride of Nietzschean proportions.

Even if we remain agnostic about Nick Bostrom’s existential risk superintelligence general AI, we can be fairly certain that we have a sociological moment of impact starting more or less yesterday.

There’s just no way new capacities of this magnitude come about with this kind of speed, and then everything just goes back to normal. For all we know, normal might never happen again.

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By definition, the word symbiosis is a term commonly used in biology to describe the relationship between two different organisms that live together in close association, and both partners benefit from the relationship.

TO A CERTAIN EXTENT THIS IS WHAT IS HAPPENING WITH THE APPLICATION OF TECHNOLOGY TO OUR LIVES, AS MANY PROBLEMS SIMPLY CANNOT BE FROMULATED OR RESOLVED WITHOUT THE HELP OF COMPUTERS.

AN OTHER WORDS:

The computers should be acting as a “serving agent,” providing the human with the information they needed to make informed decisions.

Recognized that the human mind have limitations, such as limited memory capacity and the inability to perform complex calculations quickly. Computers, on the other hand, have almost unlimited memory capacity and perform calculations at incredible speeds. By working together, humans and computers could overcome each other’s limitations and achieve a level of productivity that was not possible before.

Computers are now responsible for performing complex computations and storing vast amounts of information, while humans are be removed from making judgements and decisions based on the information provided by the computer.

One of the main objectives with the growing scale and complexity of information processing tasks of human-computer symbiosis is to bring the computer effectively into the formative parts of technical problems.

‘The question is not ‘What is the answer?’ The question is ‘What is the question?

THAT QUESTION BECOMES.   CAN WE LIVE DIGTILIZED LIVES?

Nowadays, many intelligent systems work in a symbiotic relationship with humans.

For example,

Every time we rate a movie on Netflix, we are helping artificial intelligence understand our behaviour and in the future recommend movies based on our preferences.

In the financial industry, computers are widely used to process large amounts of data in real-time, identify trading patterns, and make accurate predictions. Financial analysts rely on computational analysis to buy and sell stocks or make risky financial moves.

The market place, and its movements, which affect global economies are run by Algorithms for profit.

In the e-commerce sites we use, AI can make inferences and anticipate some tasks based on our shopping lists and recommend products. This is also a symbiotic and collaborative relationship.

Grammarly is another example of how the symbiosis between humans and computers is being utilized in the writing field. Through its AI technology, the tool is capable of suggesting real-time grammatical and spelling corrections, and the user’s experience when using it can contribute to the evolution of their ability to improve their vocabulary, as the tool offers suggestions for synonyms and more suitable word choices.

There are hundreds of other examples, but in order to build computational systems that adapt to human needs, we also need to understand how these intelligent systems work and execute tasks, and this is increasingly becoming impossible with machine learning.

Looking at the current context, the human-computer symbiosis becomes increasingly important as interactions between humans and machines become more frequent and complex, enabling users to interact with technology in a natural way.

As our interaction with intelligent systems increases every day, the principles of human-computer symbiosis are also central to living a life.

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Defining the term “Augmented Intelligence” can be quite challenging since there are many definitions.

Different researchers and practitioners tend to define it in their own unique way.

I define it as the erosion of our ability to reason for ourselves.

AI-enabled frontier technologies are helping to save lives, diagnose diseases and extend life expectancy. In education, virtual learning environments and distance learning have opened up programmes to students who would otherwise be excluded. Public services are also becoming more accessible and accountable through blockchain-powered systems, and less bureaucratically burdensome as a result of AI assistance. Big data can also support more responsive and accurate policies and programmes.

The use of algorithms can replicate and even amplify human and systemic bias where they function on the basis of data which is not adequately diverse. Lack of diversity in the technology sector can mean that this challenge is not adequately addressed.

Today, digital technologies such as data pooling and AI are used to track and diagnose issues in agriculture, health, and the environment, or to perform daily tasks such as navigating traffic or paying a bill.

They can be used to defend and exercise human rights – but they can also be used to violate them, for example, by monitoring our movements, purchases, conversations and behaviours. Governments and businesses increasingly have the tools to mine and exploit data for financial and other purposes.

Data-powered technology has the potential to empower individuals, improve human welfare, and promote universal rights, depending on the type of protections put in place.

Social media connects almost half of the entire global population.

It enables people to make their voices heard and to talk to people across the world in real time. However, it can also reinforce prejudices and sow discord, by giving hate speech and misinformation a platform, or by amplifying echo chambers.

How to manage these developments is the subject of much discussion – nationally and internationally – at a time when geopolitical tensions are on the rise. This war of information is becoming so important that it can influence democracy and the opinion of people before the vote in an election for instance.

We’re now on the verge, as a society, of appropriately recognizing the need to respect privacy in our Web 2.0 world.

In a world where everyone has an opinion and, more importantly, where everyone has the ability, if they choose, to share it with the rest of the world, one person’s hate speech can sometimes be another’s right to free speech.

Social media companies need to take “more responsibility” for what is on their platforms. There has to be a reckoning for what social media is making available [online].

IRELAND IS THE FIRST COUNTRY TO ADDRESS THE ABOVE.

As things stand in Ireland, hate speech is defined as any communication in public intended or likely to be threatening or abusive, and likely to stir up hatred against a person due to their race, colour, nationality, religion, ethnicity, Traveller origins, and/or sexual orientation. The proposed law will also make it an offence to deny or trivialise genocide. It will define a hate crime as any criminal offence which is perceived by the victim, or any other person, to have been motivated by prejudice.

The new legislation will criminalise any intentional or reckless communication or behaviour that is likely to incite violence or hatred against a person or persons because they are associated with a protected characteristic. The penalty for this offence will be up to five years’ imprisonment.

The provisions of the new legislation have been crafted to ensure that they will capture hate speech in an online context.

THIS IS THE FIRST SMALL STEP IN THE RIGHT DIRECTION TO COMBAT UNREGULATED TECHNOLOGY.

For most of the past decade, public concerns about digital technology have focused on the potential abuse of personal data.

This debate is NOW entering a new phase.

As companies increasingly embed artificial intelligence in their products, services, processes, and decision-making, attention is shifting to how data is used by the software—particularly by complex, evolving algorithms that might diagnose a cancer, drive a car, or approve a loan.

The problem crops up in many other guises:

For instance, in ubiquitous online advertisement algorithms, which may target viewers by race, religion, or gender.

Software used by leading hospitals exhibit significant racial bias to prioritize recipients of kidney transplants discriminated against Black patients.

In dealing with biased outcomes, regulators have mostly fallen back on standard antidiscrimination legislation.

That’s workable as long as there are people who can be held responsible for problematic decisions. But with AI increasingly in the mix, individual accountability is undermined.

Some algorithms make or affect decisions with direct and important consequences on people’s lives.

They diagnose medical conditions, for instance, screen candidates for jobs, approve home loans, or recommend jail sentences. In such circumstances it may be wise to avoid using AI or at least subordinate it to human judgment. Using AI could therefore increase human decision-makers’ accountability, which might make people likely to defer to the algorithms more often than they should.

The degree of trust in AI varies with the kind of decisions it’s used for. When a task is perceived as relatively mechanical and bounded—think optimizing a timetable or analysing images—software is regarded as at least as trustworthy as humans.

But when decisions are thought to be subjective or the variables change (as in legal sentencing, where offenders’ extenuating circumstances may differ), human judgment is trusted more, in part because of people’s capacity for empathy. This suggests that companies need to communicate very carefully about the specific nature and scope of decisions they’re applying AI to and why it’s preferable to human judgment in those situations. For example, in machine diagnoses of medical scans, people can easily accept the advantage that software trained on billions of well-defined data points has over humans, who can process only a few thousand.

On the other hand, applying AI to make a diagnosis regarding mental health, where factors may be behavioural, hard to define, and case-specific, would probably be inappropriate. It’s difficult for people to accept that machines can process highly contextual situations. And even when the critical variables have been accurately identified, the way they differ across populations often isn’t fully understood—which brings us to the next factor.

An algorithm may not be fair across all geographies and markets.

Just like human judgment, AI isn’t infallible. Algorithms will inevitably make some unfair—or even unsafe—decisions.

The right…to obtain an explanation of the decision reached” by algorithms, MUST BE ENSHRINNED IN LAW.

But what does it mean to get an explanation for automated decisions, for which our knowledge of cause and effect is often incomplete?

Should we require—and can we even expect—AI to explain its decisions?

However, most people lack the advanced skills in mathematics or computer science needed to understand, let alone determine whether the relationships specified in it are appropriate. And in the case of machine learning—where AI software creates algorithms to describe apparent relationships between variables in the training data—flaws or biases in that data, not the algorithm, may be the ultimate cause of any problem.

If AI starts to listen to us and adapt to our every move, we can only “win” by mirroring it, and being equally attentive to it, even to the point of treating this wild piece of silicon clockwork as though it were alive.

Because, in the end, when we don’t know where we begin and AI ends, then AI is essentially as alive as anything.

AI can only exist because it feeds on human civilization and knowledge coded into text and other digestible data — but humans are in turn subjected to the power of AI, and thus deeply reshaped by it, because AI coordinates more data than we can and knows, well, us. The AI soon knows us better than we can know it, or even know ourselves.

If we seek relational proportionality and resonance across the AI-humanity axis, we must of course also feed this intra-action with socially proportional perspectives, i.e. with social justice.

Our very civilizational sanity and survival depend upon balancing the informational diet of the AI, so that it can itself produce emergent patterns that resonate through and across societies… But the Internet is roughly as skewed and distorted as the power relations of global humanity at large.

It acts on the whole with great efficiency and speed, but it cannot speak for the whole.

What you can expect is increasing dissonance, a spiralling insanity, as the “human-AI-AI-human intra-action” system disconnects from the rest of reality, from the larger scheme that contains the actual multiplicity of the world’s perspectives.

If we don’t want to spiral into virtual madness with real social consequences, we need to balance out the reality projected into the digital realm: the encoded information. It mean’s that AI itself must be used to more proportionally and correctly represent the lives, experiences, and embodied — or intellectual — knowledge of the world.

In short, if we apply the AI to balancing out human-perspectives-as-projected-onto-the-web-as-data, not only can we get a more just and sane society; we can also help to retain an AI that remains on the sane and just side in the first place.

Or, yet more succinctly: A sane AI is also a social justice AI, but one that dodges the traps of present-day social justice and intersectionality discourses.

Let me underscore: If we fail to do this, we instead unleash AI powers that widen social gaps and fracture knowledge systems into different continents where people become entirely unable to comprehend one another, leading to social and psychological decay.

If we want a world that is not driven by digitalization ,THE TIME IS NOW TO DO SOME THING ABOUT IT.

All human comments appreciated. All like clicks and abuse chucked in the bin.

Contact: bobdillon33@gmail.com