“Artificial Intelligence” is a terminology specifically invented in 1956 by John McCarthy and concerns the ability to make appropriate generalizations quickly, but based on an inevitably limited set of data.
The wider the scope and the faster conclusions are drawn, and with minimal information, the smarter the machine’s behaviour can be defined.
Intelligence is the creative adaptation to quick changes in the environment. This is the now classic definition, but in this case, with machines, the speed and the increasingly narrow base of the starting data are also evaluated.
What if the starting data does not contain exactly the necessary information – which is possible? What if, again, the speed of the solution stems from the fact that the data collected is too homogeneous and does not contain the most interesting data?
Konrad Lorenz, the founder of animal ethology, was always very careful to maintain that between instinctive behaviour and learned behaviour, external environmental and genetic sources can be equally “intelligent”. The fact, however, is that greater flexibility of a behaviour – always within a reasonable time, but not as quickly as possible – generates greater intelligence of the animal.
As said by a great student of Lorenz, Nikko Tinbergen, human beings are “representational magpies”, which means that much of their genetic and informative history has no practical value.
When the collection of information becomes easy, the “adaptive” magpie has a very adaptive behaviour, but when the data collection is at the maximum, all data counts and we never know which, among this data, will really be put into action.
In other words, machine data processing is a “competence without understanding”, unless machines are given all senses – which is currently possible.
Human intelligence is defined when we are at the extreme of physically possible data acquisition, i.e. when individuals learn adaptive-innovative behaviour from direct imitation of abstract rules.
Abstract rules, not random environmental signals.
If machines could reach this level, they would need such a degree of freedom of expression that, today, no machine can reach, not least because no one knows how to reach this level; and how this behaviour is subsequently coded.
What if it cannot be encoded in any way?
The standardization of “if-then” operations that could mimic instincts, and of finalized operations (which could appear as an acquired Lorenz-style imprinting) is only a quantitative expansion of what we call “intelligence”, but it does not change its nature, which always comes after the particular human link between instinct, intelligence and learning by doing.
Which always has an accidental, statistical and unpredictable basis. Which duck will be the first to call Konrad Lorenz “dad”, thus creating a conditioning for the others? No one can predict that.
If systematized, bio-imitation could be a way to produce – in the future – sentient machines that can create their own unique and unrepeatable intelligent way to react to the environment, thus creating a one and only intelligent behaviour. Will it be unique?
However, let us go back to Artificial Intelligence machines and how they work.
In the 1980s there was the first phase of large investment in AI, with the British Alvey Program; the U.S. DARPA Program spending a billion US dollars on its Strategic Computing Initiative alone; finally the Japanese Fifth Generation Computer Project, investing a similar amount of money.
At the time there was the booming of “expert systems”, i.e. symbolic mechanisms that solved problems, but in a previously defined area.
From the beginning, expert systems were used in financial trading.
There was the hand of the expert system in the fall of the Dow Jones Industrial Average by 508 points in 1987. In 1990, however, Artificial Intelligence also began to be used in the analysis of financial frauds, with an ad hoc program used by the Financial Crimes Enforcement Network (FinCEN), especially with the possibility to automatically review 200,000 transactions per week and to identify over 400 illegal transactions.
Machine learning, the model on which the most widely used AI financial technology relies, is based on a work by McCullogh and Pitts in 1943, in which it was discovered that the human brain produces signals that are both digital and binary.
A machine learning system is composed, in principle, by: 1) a problem; 2) a data source; 3) a model; 4) an optimization algorithm; 5) a validation and testing system.
In 2011, deep learning (DL) added to the other “expert” systems.
It is a way in which machines use algorithms operating at various separate levels, as happens in the real human brain. Hence deep learning is a statistical method to find acceptably stable paradigms in a very large data set, by imitating our brain and its structure in layers, areas and sectors.
As explained above, it is a mechanism that “mimics” the functioning of the human brain, without processing it.
DL could analyse for the first time non-linear events, such as market volatility, but its real problem was the verification of models: in 2004 Knight Capital lost 440 million US dollars in 45 minutes, because it put into action a DL and financial trading model that had not been tested before.
In 2013, during a computer block of only 13 minutes, Goldman Sachs flooded the U.S. financial market with purchase requests for 800,000 equities. The same week., again for a computer error, the Chinese Everbright Securities bought 4 billion of various shares on the Shanghai market, but without a precise reason.
Between 2012 and 2016, the United States invested 18.2 billion US dollars in Artificial Intelligence, while only 2.6 were invested by China and 850 million US dollars by the United Kingdom in the same period.
The Japanese Government Pension Savings Investment Fund, the world’s largest pension fund manager, thinks it can soon replace “human” managers with advanced Artificial Intelligence systems.
BlackRock has just organized an AILab.
In 2017, however, China overtook the United States in terms of AI startups, with 15.2 billion funding.
China now has 68% of AI startups throughout Asia, raising 1.345 billion US dollars on the markets for their take-off.
China has also overtaken the United States in terms of Artificial Intelligence patents over the last five years.
Nevertheless, considered together, the USA and China still account for over 50% of all AI patents worldwide.
China also dominates the market of patents on AI technology vision systems, while deep learning data processing systems are now prey to the big global companies in the sector, namely Microsoft, Google and IBM. Similar Chinese networks are rapidly processing their new “intelligent” data collection systems, also favoured by the fact that the Chinese population is about twice as much as the US population and hence the mass of starting data is huge.
The Chinese intelligence industry zone near Tianjin is already active.
In the end, however, how does Artificial Intelligence change the financial sector?
AI operates above all in the trading of securities and currencies in various fields: algorithmic trading; the composition and optimization of portfolios; validation of investment models; verification of key operations; robo-advising, namely robotic consultancy; the analysis of impact on the markets; the effectiveness of regulations and finally the standard banking evaluations and the analysis of competitors’ trading.
Algorithmic trading is a real automatic transaction system – a Machine Learning program that learns the structure of transaction data and then tries to predict what will happen.
Nowadays computers already generate 70% of transactions in financial markets, 65% of transactions in futures markets and 52% of transactions in the public debt securities market.
The issue lies in making transactions at the best possible price, with a very low probability of making mistakes and with the possibility of checking different market conditions simultaneously, as well as avoiding psychological errors or personal inclinations.
In particular, algorithmic trading concerns hedge funds operations and the operations of the most important clients of a bank or Fund.
There are other AI mathematical mechanisms that come into play here.
There is, in fact, signal processing, which operates by filtering data to eliminate disturbing elements and observe the development trends of a market.
There is also market sentiment.
The computer is left completely unaware of the operations in progress, until the specific algorithm is put to work – hence the machine immediately perceives the behaviour of supply and demand.
There is also the news reader, a program that learns to interpret the main social and political phenomena, as well as pattern recognition, an algorithm teaching the machine to learn and react when the markets show characteristics allowing immediate gains.
Another algorithm is available, developed by a private computer company in the USA, which processes millions of “data points” to discover investment models or spontaneous market trends and operates on trillions of financial scenarios, from which it processes the scenarios deemed real.
Here, in fact, 1,800 days of physical trading are reduced to seven minutes.
However, the algorithms developed from evidence work much better than human operators in predicting the future.
Artificial Intelligence works as a prediction generator even in the oldest financial market, namely real estate.
Today, for example, there is an algorithm, developed by a German company, that automatically “extracts” the most important data from the documents usually used to evaluate real estate transactions.
In Singapore, Artificial Intelligence is used to calculate the value of real estate property, with a mix of algorithms and comparative market analysis. Man is not involved at all.
As to corporate governance, there are AI programs that select executives based on their performance, which is analysed very carefully.
What is certainly at work here is the scientist and naive myth of excluding subjectivity, always seen as negative. The program, however, is extremely analytical and full of variables.
Artificial Intelligence is also used in the market of loans and mortgages, where algorithms can be processed from an infinity of data concerning clients (age, work, gender, recurrent diseases, lifestyles, etc.) and are linked to operations – always through an algorithm – which are ordered, without knowing it, from one’s own mobile phone or computer.
So far we have focused on Artificial Intelligence algorithms.
But there is also quantum computing (QC), which is currently very active already. Its speed cannot be reached by today’s “traditional” computers.
It is a more suitable technology than the others to solve problems and make financial forecasts, because QC operates with really random variables, while the old algorithms simply simulate random variables.
Quantum computing can process several procedures simultaneously, and these “coexistence states” are defined as qubits.
In a scenario analysis, QC can evaluate a potentially infinite set of solutions and results that have been randomly generated.
An extremely powerful machine which, however, cannot determine exactly – as it also happens to slower machines – whether the scenario processed corresponds to human interests (but only to the initial ones known by the machine) or whether the procedure does not change during operations.
2022: Rise of Economic Power of Small Medium Businesses across the World
Why mirrors of the Wall: To fight obesity a life-sized mirror required, to uplift the national economy a simple calculator is a critical necessity. Only, right amounts in right columns, correctly totaled show a balanced picture. In the coming days, pandemic will become endemic; the same day, all over the world, nations will suddenly start announcing economic pandemic. Observe, lingering global economic chaos still masked hiding a troubled face. As a proof, observe the absence of bold open economic strategies or real action plans.
Why lead, follow or get out of the way: Our hyper-digitized world has now openly exposed; meritocracy-centric and mediocrity-driven nations. In this global race, no nations are the same; but rules of engagement on productivity, performance and profitability and entrepreneurial behaviors are almost identical. If economic survival to save nations is critical, still why in most nations the tasks of economic development mandated to teams critically lacking the required entrepreneurial and job creator mindsets. Nations with mastery on national mobilization of entrepreneurialism will lead; others may follow or get out of the way.
Why the two wheels: What will it take for nations to immediately start upskilling their front line economic development teams on a fast track basis. How can they create real SME growth, teach the teams on real tactical battlefields to wrestle, and harness real entrepreneurialism. Otherwise, repeating already broken models under crypto-illusions speaks volume on core competency. A great future is unfolding for job seeker and job creator minds must come together as two wheels of the same cart on national economic development.
Why the wrong building: Study, why are ‘population-rich-nations’ growing in economic prosperity much faster than ‘knowledge rich nations’? Why, if you bifurcate ‘developed nations’ and ‘emerging-nations’ the emerging nations are advancing much faster. Now, when you apply a basic calculator, the ‘SME of any nation’ in the world will save the national economies but not the ‘big-business of the nation’. Study more on Google, discover the reasons, and acquire your own knowledge on such new affairs. Most importantly, if these topics still not openly discussed in your surroundings you are already in the wrong building.
Why the triangulation: To triangulate, the mastery of ‘national mobilization of entrepreneurialism’ with national SME verticals and exportability will outline the blueprints to save national economies. How will the rise of the small medium business economy not only create local grassroots prosperity but also make national citizenry happy and stable.
Why the needed adjustments: Understanding of local economic landscape; traditionally, despite being a small tax contributor, big business is allowed to stomp all over its own government, while the SME sector, the largest tax contributor of any nation, is crushed and neglected. Technology is changing this fast, SME of the world now have the tools once only available to large empires, global access reserved for large scale maneuvers now a new digitized world of micro-trade, micro-manufacturer and micro-exports will create a new tidal wave of global commerce.
Why the absence of calculator: What is stopping any political leadership to declare national mobilization of entrepreneurialism and identify IK to 1000K SME with USD$1 million to USD$10 million in annual turnover, on digital platforms of upskilling exporters and reskilling manufacturers and double or quadruple their growth in 1-2 years. Is it the absence of a calculator, domination of job seekers and non-entrepreneurial mindsets, or hidden fears of big business not allowing such massive uplift? The near future calls for digitized economies and upskilled citizenry, as basic perquisites for any functioning nation.
Why fears of the pie: Hence, the tremors in the global boardrooms and still little or no response on uplifting the tides of SME in various corresponding verticals around the world, for fears of upsetting the top leaders. Ask the big forbidden questions; why will super big players ever allow the emergence of many millions sleek, technologically advanced and global-age skilled SME to grow to only chip away their own power play and half of their pie? It may be true in some regions, but there are grassroots benefits in such advancements provided there are right mindsets and matching vision of the nation.
Why the two new forces: Hence, there exists the low-level mediocre SME economic development across the world, where lip service fills the gaps and academic studies create colorful charts and circles to point confusion and trade groups comply to remain in deep silence. The SME of the world will rise in economic power, across the world as a new world dawns. The power is already hidden in two unstoppable forces; first the technology and second the global connectivity of opinions and knowledge. Both combined now allows some 500 million SME to organize and billions displaced rejecting cubical slavery drawn into out the box entrepreneurialism. It is the easiest time across the world to dance on entrepreneurial platforms.
Why history repeats: On the course of history, no other experiment of human journey is as successful as that of Americans and how when some 100K entrepreneurs carved the image-supremacy of entrepreneurialism to last well over a century. During the same period in Europe and Asia followers of such out of the box thinkers were not only rejected by society, but also jailed as a liability to society. Nations must identify and create an ‘umbrella of entrepreneurialism’ to preserve and respect the drivers and proponents of such intellectualism and avoid such notions caught in fakery. Today Asia alone has created 500 million new entrepreneurs during the last decade. Ignoring this by any nation in the world will simply sink them.
Why the alpha dreamers: The five billion connected alpha dreamers have learned new lessons during the last 500 days; they witnessed the handling of pandemic and are now ready to study the unfolding of global economic pandemic. They realize the serious limitations of old style administrations, the inequalities, the injustice and lack of skills to cope with futurism. Covidians, the survivors of the pandemic, now vote in some 100 national elections scheduled over the next 500 days. A new way of thinking is emerging. Every day the global news increasingly focused on self-inflicted disasters and absence of corrective new measures to advance for better grassroots prosperity.
Why the next elections: Any naivety on ignoring this post pandemic metamorphism will backfire during next national elections. The national public opinion has now turned into global opinion; the populace of one country supporting the populace of another country for being under influences of the populace in a third or fourth country. Last decade our local streets molded public opinion; today global streets are doing just that. Deeply study how five billion connected slowly are forming the largest mindshare ever assembled. How all this does translates to local/global issues and what level of expertise needed to tackle bigger issues.
Why the soft power assets: The biggest losses of the nations of today are not at all their accumulated debts but continuously having greater losses of missed opportunities on the global stage. The lack of inability to recognize the soft power of a nation today is way above just the notion of culture, politics and foreign policy; it is far more extended and about nation-building, upskilling citizenry and pursuing common good.
Why broken systems: When tax laws are universally broken,universally criticized but universally remain unchanged; when there is no single supreme power left as all deemed declared useless, therefore, this calls for a major change but not from the very top rather grows from the very bottom. When economic progress remains as number one priority, why is it that only job seekers drive such economic development programs while job creator mindsets are critically ignored? Bringing both mindsets closer as a mandated agenda will bring hidden magic to the goals.
Why the deep silence: Quick test on your local economic resilience: right now, what parts of such narratives are your local governments openly engaging and deploying? What types and styles of small medium business mobilization are on the go? What level of entrepreneurialism drives ever created under what agenda? What is happening to upskilling and reskilling including women entrepreneurial drives? What level of authoritative analysis on the table to upskill current economic development teams? If most of these issues are often not new funding dependent but mobilization hungry and execution starved, why are economic development teams so scared? Is your local economy prospering? Maybe you are already far ahead. Study on Google how Expothon is gaining global attention and tabling Cabinet Level workshops and virtual events on revival of the SME power as an immediately deployable strategy to save and uplift national economies.
Why fears of facing clarity: Is this why economic development teams are so afraid? Will such ideas alter government agencies and their mandates in the future? Is this how Meritocracy will drive out Bureaucracies? Is this where the new future of economic prosperity hidden? Is this how we will advance to catch up with lost time and opportunities? Is this how nations will finally optimize already hidden talents in their national trade groups, chambers and governments to full capacity? Is this how we will eventually open new bold discussions on distribution of right intellectualism to fit the right needs of humankind?
Suddenly, how far has our world moved on; bandaged, stitched and altered in thinking, psyche damaged but still aware of common sense. Our understanding of humanity is perhaps now in search of common good. To liberate itself from strangle of old thinking, the SME economic development world urgently needs major adjustments to bring balance between job seeker mindsets with job creator mindsets. Start immediately with a quick test across the economic development departments and measure such imbalances. Study more on Google. The rest is easy.
Can e-commerce help save the planet?
If you have logged onto Google Flights recently, you might have noticed a small change in the page’s layout. Alongside the usual sortable categories, like price, duration, and departure time, there is a new field: CO2 emissions.
Launched in October 2021, the column gives would-be travellers an estimate of how much carbon dioxide they will be responsible for emitting.
“When you’re choosing among flights of similar cost or timing, you can also factor carbon emissions into your decision,” wrote Google’s Vice President of Travel Products, Richard Holden.
Google is part of a wave of digital companies, including Amazon, and Ant Financial, encouraging consumers to make more sustainable choices by offering eco-friendly filter options, outlining the environmental impact of products, and leveraging engagement strategies used in video games.
Experts say these digital nudges can help increase awareness about environmental threats and the uptake of solutions to reduce greenhouse gas emissions.
“Our consumption practices are putting tremendous pressure on the planet, driving climate change, stoking pollution and pushing species towards extinction,” says David Jensen, Digital Transformation Coordinator with the United Nations Environment Programme (UNEP).
“We need to make better decisions about the things we buy and trips we take,” he added. “These green digital nudges help consumers make better decisions as well as collectively drive businesses to adopt sustainable practices through consumer pressure.”
At least 1.5 billion people consume products and services through e-commerce platforms, and global e-commerce sales reached US$26.7 trillion in 2019, according to a recent UN Conference on Trade and Development (UNCTAD) report.
Meanwhile, 4.5 billion people are on social media and 2.5 billion play online games. These tallies mean digital platforms could influence green behaviors at a planetary scale, says Jensen.
One example is UNEP-led Playing for the Planet Alliance, which places green activations in games. UNEP’s Little Book of Green Nudges has also led to more than 130 universities piloting 40 different nudges to shift behaviour.
A 2020 study by Globescan involving many of the world’s largest retailers found that seven out of 10 consumers want to become more sustainable. However, only three out of 10 have been able to change their lifestyles.
E-commerce providers can help close this gap.
“The algorithms and filters that underpin e-commerce platforms must begin to nudge sustainable and net-zero products and services by default,” said Jensen. “Sustainable consumption should be a core part of the shopping experience empowering people to make choices that align with their values.”
Embedding sustainability in tech
Many groups are trying to leverage this opportunity to make the world a more sustainable place.
The Green Digital Finance Alliance (GDFA), launched by Ant Group and UNEP, aims to enhance financing for sustainable development through digital platforms and fintech applications. It launched the Every Action Counts Coalition, a global network of digital, financial, retail investment, e-commerce and consumer goods companies. The coalition aims to help 1 billion people make greener choices and take action for the planet by 2025 through online tools and platforms.
“We will bring like-minded members together to experiment with new innovative business models that empower everyone to become a green digital champion,” says Marianne Haahr, GDFA Executive Director.
In one example, GDFA member Mastercard, in collaboration with the fintech company Doconomy, provides shoppers with a personalized carbon footprint tracker to inform their spending decisions.
In the UK, Mastercard is partnering with HELPFUL to offer incentives for purchasing products from a list of over 150 sustainable brands.
Mobile apps like Ant Forest, by Ant Group, are also using a combination of incentives and digital engagement models to urge 600 million people make sustainable choices. Users are rewarded for low-carbon decisions through green energy points they can use to plant real trees. So far, the Ant Forest app has resulted in 122 million trees being planted, reducing carbon emissions by over 6 million tons.
Three e-commerce titans are also aiming to support greener lifestyles. Amazon has adopted the Climate Pledge Friendly initiative to help at least 100 million people find climate-friendly products that carry at least one of 32 different environmental certifications.
SAP’s Ariba platform is the largest digital business-to-business network on the planet. It has also embraced the idea of “procuring with purpose,” offering a detailed look at corporate supply chains so potential partners can assess the social, economic and environmental impact of transactions.
“Digital transformation is an opportunity to rethink how our business models can contribute to sustainability and how we can achieve full environmental transparency and accountability across our entire value chain,” said SAP’s Chief Sustainability Officer Daniel Schmid.
UNEP’s Jensen says a crucial next step would be for mobile phone operating systems to adopt standards that would allow apps to share environment and carbon footprint information.
“This would enable people to seamlessly calculate their footprints across all applications to develop insights and change behaviours,” Jensen said. “Everyone needs access to an individual’ environmental dashboard’ to truly understand their impact and options for more sustainable living.”
Need for common standards
As platforms begin to encode sustainability into their algorithms and product recommendations, common standards are needed to ensure reliability and public trust, say experts.
Indeed, many online retailers are claiming to do more for the environment than they actually are. A January analysis by the European Commission and European national consumer authorities found that in 42 per cent, sustainability claims were exaggerated or false.
In November, the One Planet network issued guidance material for e-commerce platforms that outlines how to better inform consumers and enable more sustainable consumption, based on 10 principles from UNEP and the International Trade Centre.
The European Union is also pioneering core standards for digital sustainability through digital product passports that contain relevant information on a product’s origin, composition, environmental and carbon performance.
“Digital product passports will be an essential tool to strengthen consumer protection and increase the level of trust and rigour to environmental performance claims,” says Jensen. “They are the next frontier on the pathway to planetary sustainability in the digital age.”
2022: Small Medium Business & Economic Development Errors
Calling Michelangelo: would Michelangelo erect a skyscraper or can an architect liberate David from a rock of marble? When visibly damaged are the global economies, already drowning their citizenry, how can their economic development departments in hands of those who never ever created a single SME or ran a business, expect anything else from them other than lingering economic agonies?
The day pandemic ends; immediately, on the next day, the panic on the center stage would be the struggling economies across the world. On the small medium business economic fronts, despite, already accepted globally, as the largest tax contributor to any nation. Visible worldwide, already abandoned and ignored without any specific solutions, there is something strategically wrong with upskilling exporters and reskilling manufacturers or the building growth of small medium business economies. The SME sectors in most nations are in serious trouble but are their economic development rightly balanced?
Matching Mindsets: Across the world, hard working citizens across the world pursue their goals and some end up with a job seeker mindset and some job creator mindset; both are good. Here is a globally proven fact; job seekers help build enterprises but job creators are the ones who create that enterprise in the first place. Study in your neighborhoods anywhere across the world and discover the difference.
Visible on LinkedIn: Today, on the SME economic development fronts of the world, clearly visible on their LinkedIn profiles, the related Ministries, mandated government departments, trade-groups, chambers, trade associations and export promotion agencies are primarily led by job seeker mindsets and academic or bureaucratic mentality. Check all this on LinkedIn profiles of economic development teams anywhere across the world.
Will jumbo-pilots do heart transplant, after all, economic performance depends on matching right competency; Needed today, post pandemic economic recovery demands skilled warriors with mastery of national mobilization to decipher SME creation and scalability of diversified SME verticals on digital platforms of upskilling for global age exportability. This fact has hindered any serious progress on such fronts during the last decade. The absence of any significant progress on digitization, national mobilization of entrepreneurialism and upskilling of exportability are clear proofs of a tragically one-sided mindset.
Is it a cruise holiday, or what? Today, the estimated numbers of all frontline economic development team members across 200 nations are roughly enough to fill the world-largest-cruise-ship Symphony that holds 6200 guests. If 99.9% of them are job-seeker mindsets, how can the global economic development fraternity sleep tonight? As many billion people already rely on their performances, some two billion in a critical economic crisis, plus one billion starving and fighting deep poverty. If this is what is holding grassroots prosperity for the last decade, when will be the best time to push the red panic button?
The Big Fallacy of “Access to Finance” Notion: The goals of banking and every major institution on over-fanaticized notions of intricate banking, taxation are of little or no value as SME of the world are not primarily looking for “Access to Capital” they are rather seeking answers and dialogue with entrepreneurial job creator mindsets. SME management and economic development is not about fancy PDF studies of recycled data and extra rubber stamps to convince that lip service is working. No, it is not working right across the world.
SME are also not looking for government loans. They do not require expensive programs offered on Tax relief, as they make no profit, they do not require free financial audits, as they already know what their financial problems are and they also do that require mechanical surveys created by bureaucracies asking the wrong questions. This is the state of SME recovery and economic development outputs and lingering of sufferings.
SME development teams across the world now require mandatory direct SME ownership experiences
The New Hypothesis 2022: The new hypothesis challenges any program on the small medium business development fronts unless in the right hands and right mindsets they are only damaging the national economy. Upon satisfactory research and study, create right equilibrium and bring job seeker and job creator mindsets to collaborate for desired results. As a start 50-50, balances are good targets, however, anything less than 10% active participation of the job creator mindset at any frontline mandated SME Ministry, department, agency or trade groups automatically raises red flags and is deemed ineffective and irrelevant.
The accidental economists: The hypothesis, further challenges, around the world, economic institutes of sorts, already, focused on past, present and future of local and global economy. Although brilliant in their own rights and great job seekers, they too lack the entrepreneurial job creator mindsets and have no experience of creating enterprises at large. Brilliantly tabulating data creating colorful illustrative charts, but seriously void of specific solutions, justifiably as their profession rejects speculations, however, such bodies never ready to bring such disruptive issues in fear of creating conflicts amongst their own job seeker fraternities. The March of Displaced cometh, the cries of the replaced by automation get louder, the anger of talented misplaced by wrong mindsets becomes visible. Act accordingly
The trail of silence: Academia will neither, as they know well their own myopic job seeker mindset. In a world where facial recognition used to select desired groups, pronouns to right gatherings, social media to isolate voting, but on economic survival fronts where, either print currency or buy riot gears or both, a new norm; unforgiveable is the treatment of small medium business economies and mishmash support of growth. Last century, laborious and procedural skills were precious, this century surrounded by extreme automation; mindsets are now very precious.
Global-age of national mobilization: Start with a constructive open-minded collaborative narrative, demonstrate open courage to allow entrepreneurial points of views heard and critically analyze ideas on mobilization of small mid size business economies. Applying the same new hypotheses across all high potential contributors to SME growth, like national trade groups, associations and chambers as their frontline economic developers must also balance with the job creator mindset otherwise they too become irrelevant. Such ideas are not just criticism rather survival strategies. Across the world, this is a new revolution to arm SME with the right skills to become masters of trade and exports, something abandoned by their economic policies. To further discuss or debate at Cabinet Level explore how Expothon is making footprints on new SME thinking and tabling new deployment strategies. Expothon is also planning a global series of virtual events to uplift SME economies in dozens of selected nations.
Two wheels of the same cart: Silence on such matters is not a good sign. Address candidly; allow both mindsets to debate on how and why as the future becomes workless and how and why small medium business sectors can become the driving engine of new economic progress. Job seekers and job creators are two wheels of the same cart; right assembly will take us far on this economic growth passage. Face the new global age with new confidence. Let the nation witness leadership on mobilization of entrepreneurialism and see a tide of SME growth rise. The rest is easy.
King Mohammed VI of Morocco launches Pan-African Giant Vaccine Production Plant
Morocco is getting ready to produce its own vaccines. In Benslimane, King Mohammed VI kicked off on Thursday 27th of...
Environment contaminated with highly toxic substances, risking the health of nearby communities
New research published today by Zero Waste Europe (ZWE) about incinerators in three countries – Spain, Czechia, and Lithuania –...
Shaking Things Up: A Feminist Pakistani Foreign Policy
Almost eight years ago, under Foreign Minister Margot Wallstrom in 2014, Sweden created its first of a kind feminist foreign...
Indonesia’s contribution in renewables through Rare Earth Metals
The increasing of technological advances, the needs of each country are increasing. The discovery of innovations, the production of goods...
Test of Babur Cruise Missile: Pakistan Strengthening its Strategic Deterrence
A month of December 2021 Pakistan successfully tested “indigenously developed” Babur cruise missile 1b. In this recent test, Pakistan enhanced...
The Middle East Rush to Bury Hatchets: Is it sustainable?
How sustainable is Middle Eastern détente? That is the $64,000 question. The answer is probably not. It’s not for lack...
Scientists turn underwater gardeners to save precious marine plant
Whoever said there’s nothing more boring than watching grass grow, wasn’t thinking about seagrass. Often confused with seaweeds and rarely...
International Law4 days ago
Psychology of Political Power : Does Power Corrupt or is Magnetic to the Most Corruptible?
East Asia4 days ago
Shi Maxian’s trap vs Thucydides’ trap
Middle East3 days ago
Embarking on Libya’s Noble Foray Into the Future
East Asia3 days ago
“Post-Communism Era”, “Post-Democracy Era”, in the face of “authoritarian liberalism”
Southeast Asia3 days ago
Spreading Indonesia’s Nation Branding Through “Kopi Kenangan”
East Asia3 days ago
The role of China in fighting of fascism and racism
East Asia3 days ago
The American politicization of the Beijing Winter Olympics, and the “post-truth era” theory
Eastern Europe4 days ago
The Stewards of Hate