AI: Solution or Problem?

Artificial Intelligence: Solution or Problem?

An Appeal to Develop Conscious Communication and Metrics


The Context: Corinium Intelligence promotes Connected Thinking. 1

Physics and Mathematics as Overarching Sciences. 2

Science vs Religion or Knowing vs Believing. 2

The Medium is Message and Messenger 4

Science vs Technology. 5

Human vs Artificial Intelligence. 7

Is Time really Money?. 7

Quantity vs Quality – of Jobs and other Subjects of Measuring. 8

Digital is Individual and Intelligence comes from Learning by Doing. 10

The Context: Corinium Intelligence[1] promotes Connected Thinking

The Wikipedia entry[2] about Artificial Intelligence [AI] is very comprehensive regarding all facets that contribute to human intelligence ‘externalised’ into digital machines and ‘cognitive agents’.

However, to deepen my understanding of the state of the art of AI and Machine Learning [ML], I watched about a dozen TED talks. I also spoke with Corinium’s Martin Docherty[3] thanks to their excellent conference for Chief Analytics Officers[4] where I facilitated a Discussion Group about Turning Data into Insights and Intelligence.[5]

And I read Martin’s articles on LinkedIn:

In the first article, Martin expands on the Greek theorem All things are atoms. In the second, on the pain that change is creating in thinking and feeling.

In the third article he quotes Noam Chomsky who distinguishes between two types of AI. His type 1 effectively refers to software emulating human intelligence, while his type 2 describes hardware such as robots.

Both are hailed to free humanity from laborious tasks by their evangelists and dreaded as taking jobs away by others. And there are those of us who see a digital renaissance coming where data (and images) are interpreted as reflections of reality that we can make sense of in new ways.

Physics and Mathematics as Overarching Sciences

I am writing as a female mathematician who used to diagnose software at CERN, the European Centre for Nuclear Research. In Geneva I could live my love of languages with my love of programming. In that spirit of combining human and machine languages, I see a digital renaissance[9] looming to which I am contributing with unique software methods that combine

  • the physics of All things are atoms
  • with Everything is Number by the mathematician Pythagoras, i.e. another fundamental statement we inherited from ancient Greece.

With respect to the relationship between mathematics as a model for the physical world, I discovered an Einstein quote that is relevant to today’s efforts of using data for informed decision making and driving digital transformations across organisations.

But do we try to fit our data to pre-conceived models or can we see what our data tells us?

When I came to CERN, I thought that scientists there know about god, as they know about the smallest of all things, atoms, in the largest of all, the universe.

Since then, I discovered that nuclear physicists cannot speak with astro-physicists, as they don’t use the same vocabularies. But what they have in common is their search to understand the invisible energies that connect all phenomena at smallest and largest scales.

Science vs Religion or Knowing vs Believing

The Australian journalist Margaret Wertheim wrote a fascinating history about god, physics and the gender wars that she entitled Pythagoras’ Trousers. It explains beautifully how our search for meaning is not satisfied by either religion or science.

Science is not only separated between the physics before our eyes and the mathematics behind our eyes. It is separated into more and more disciplines – without the Connected Thinking that Corinium stands for. Whole systems thinking is hardly taught in any of our educational institutions.

Instead, academics learn more and more about less and less. As a result, expert knowledge, together with skills for the job market, determines where we find our place along the spectrum of opportunities between employment, consultancy, entrepreneurship and unemployment.

Yes, God’s finger[10] in the Sistine Chapel by Michelangelo has been replaced by robots, as machines are always cheaper than people.

But is money a morally defensible justification?

Has god really been replaced by a robot, if we think of god as a word for the intelligence of the universe that embeds us on our planet in our galaxy?

Does this imply we need to think of ourselves as being replaceable by machines? Shouldn’t we raise our energies and rise in defence of our existence?

Interestingly, another book by Margaret Wertheim is called The Pearly Gates of Cyberspace[11] – A History of Space from Dante to the Internet – which asks: How did we get from seeing ourselves in soul-space (the world of Dante and the late-medievals) to seeing ourselves purely in body-space (the world of Newton and Einstein)?

Technology[12] is the “science of craft”: the knowledge of tools. Digital Technology includes the knowhow of using software that organises, manipulates and visualises data.

Data can have many sources and formats, as expressions of our thoughts and feelings takes on many styles. Considering the advantages of human over artificial intelligence, we need to bring in the consciousness and intentions which we apply to achieve the outcomes of our creative ideas and technological results. Computers don’t know morals or ethics. We surely must not succumb.

But can we believe enough in ourselves to trust our knowledge and understanding, our intuition, ingenuity, and our willingness to look for data and learn from information and the tools that help us organise and make sense?

Can we steer our mind confidently along our own way of discovery, sense-making, evaluations and decisions?

Can we replace religion with faith in ourselves? Pythagoras said Thou thyself shalt be thine god!

Can we replace preconceived scientific notions with accurate perceptions of what data visualisations show us?

Can we use collaborative tools to co-create ‘wise repositories’ of

  • software – based on recommendations from user experience – not marketing hype;
  • data – as global benchmarks for corporate financial activities – comparing ethical governance with staff exploitation and tax evasion?

How many apps do we need to try to add to our scientific understanding the technical knowhow to learn from data and images as reflections of activities in our world?

In addition to books, films and videos, we now have software packages and software languages for honing our thinking and creating world views in which we find our place and purpose. In addition to critical reviews, we have ratings, likes, shares and comments. What is the basis for our own judgment? What makes us feel secure rather than uncertain?

The Medium is the Message and the Messenger

In 1967, The Medium is the Massage by Marshall McLuhan was published with that title, because a frequent quote of his was: The Medium is the Message.

As a woman I can’t help wonder why there is not also a man with LOVE written over his body. Don’t we seek love equally, but in ways that are highly polarised, yet complementary, just as sperms compete madly while eggs sit and wait?

Pierre Collet[13] shows in his TED talk about ‘Artificial Evolution [AE] + AI agents that move like sperms.

Media carrying messages have abounded since McLuhan explored their effects on our minds as an ongoing and underlying process. The advent of computers has not only brought us new software as messengers but also new authorities. Screens and the programmers behind them are ‘authority’ in addition to authors of book, writers of film scripts and the Law.

Video publishers compete with TV presenters. But who knows best? Who knows what is right for us as individuals and our organisation? Which software represents our data best, especially when I come along and turn Excel charts into layers along a new kind of axis giving us new kinds of perspectives?


My offline prototype shows unsorted and sorted layers along a ‘visual z-axis’


Our online engine shows layered data series as a movable object in ‘Visual 3D’ 

These new visualisation styles are the result of translating software-aided thinking into programming. Both are highly individual and creative processes – just as writing, blogging and web publishing.

Corinium’s article Creativity is so 2016 – now it’s all about Resonance[14] suggests that the context for us as consumers begins to be ethics and values: related links, sites and events where ‘related’ is based on similarity of context rather than content. The context is provided by cultural beliefs, our egoistic or altruistic values as well as corporate social responsibility and corporate ethics. Corporate ethics is expressed in mission statements. But would there be whistleblowers if staff lived up to their ethics? Should we maybe focus on conscious communication and effective listening before thinking that AI and predictive analytics will allay our insecurities?

This is the power of Digital Transformation: it changes society by changing the individual
and creates new fields of resonance that are palpable thanks to screen-based technologies.


This is the resonance image of Corinium’s article on Creativity and Resonance[15]

re-visualised in True Colour 3D[16] as a movable object in different lights.

What does it mean that we can re-visualise 2D images in a new kind of 3D? What is the disruption to our thinking? What new discoveries can we make at microscopic and telescopic scales?

What conclusions can we come to that AI would not follow, even with its way of ‘Deep Learning’?

Is the visualisation of the numerical representation maybe ethically more desirable, technologically more significant and scientifically more useful than the production of drones?

What is the resonance between the content of images and the patterns and details that we see?

How do we interpret this unexpected input to our brains, as we’ve never seen anything like it before?

What does Renaissance Woman Mona Lisa tell us when she opens her eyes for us to see, as we tilt the re-visualisation of her painting? Maybe that there is no time? There is only change?

Science vs Technology

I LOVE computers and am among 12% of women in STEM [Science, Technology, Engineering and Mathematics]. When I listened to TED talks on AI, YouTube, in its ‘artificial wisdom’, presented me Lauren Schnipper[17] as the only female speaker. She appeals to develop our thinking skills as the solution to coping with the world we live in. All male presenters described what they see happening by people being replaced by machines, speculating about the resulting future.

However, there was also Juan Benet[18] who designed the Inter-Planetary File System[19] in a way that connects his philosophy and social ideals with his everyday job that announces The Next Internet Revolution[20].

It promises:

  1. decentralisation and crypto-currencies;
  2. ‘smart contracts’ as the first step to programmable law;
  3. world-wide private currencies;
  4. and Public Verifiability replacing the waning trust in public authorities.

This design for decentralised internet storage is the antidote to corporate Big Brother governance. Juan closes his presentation with

“Do you want a world that is centrally controlled?

Do you want a web that reflects that?

Or do you want a decentralised free one? It’s completely up to you!”

Lauren Schnipper[21] is working at Facebook on the Media Team, leading partnerships with digital talent and comedians. She describes our world as being VUCA: Volatile, Uncertain, Complex and Ambiguous and advocates the development of:

  1. Critical Thinking and Analytical Reasoning: skills of sense making and decision taking;
  2. Emotional / social intelligence;
  3. Novel and adaptive thinking – outside the box – beyond the norm;
  4. Cross-cultural competency;
  5. Computational thinking;
  6. Statistical analysis and quantitative reasoning;
  7. New media;
  8. Trans-disciplinary approaches.

All in all, whole human beings able to express themselves to the fullest of knowing and feeling, of connecting domains of thought or acting as jack of all trades, as Martin wrote. Are we talking about Digital Generalists as Renaissance People?

Human vs Artificial Intelligence

Lauren Schnipper’s intelligence areas cover computational thinking, communicating and reasoning as the basis for human intelligence. They do not include programming as the skill necessary to create artificial intelligence, i.e. software that writes itself – just as the sorcerer’s apprentice who could not control the forces he unleashed. However, any programming language teaches us LOGICAL thinking. I even wrote an article ages ago that programming should be accepted as mathematical method of proof. But before the web and outside academia, it just satisfied my desire to express my thinking as l’art pour l’art[22] – a piece of self-motivated work – more art outside the frame than science inside the box.

Human speech evolved into writing as uninterrupted, slowed down thinking and talking. coding developed as typing to machines with instant feedback on screens.

At CERN, physicists develop theories and build experiments to prove or disprove them. It took them ages to accept the usefulness of mainframe computers 50 years ago.

Today, Data Officers know the details of data bases and classification of files. Analytics Officers know about the software tools that help them organise flows of information on a day-to-day basis. They are expected to help the Executive make decisions about time affecting staff as stakeholders and money as passive income for shareholders.

That is where our thinking is guided by Time is Money as an unquestioned dogma.

Can we question at board levels across the globe how our ethical and social responsibility includes our staff? What priority do we give to our shareholders? What are our respective resonance fields?

Do meetings between our Data, Analytics and Executive Officers include investors and define which input is relevant so that we get significant information on a regular basis? How do we distil this information into executive summaries, conclusions and strategies from high level perspectives?

Does our C-suite hover at the cutting edge of Digital Transformation using the best possible tools to surf the wave of leading edge software? How do we discern between what is truly useful and eye opening or just another gimmick doing more of the same?

Data is food for software as processors. We need best quality food for optimally assessed processors –
with the ability to customise at individual and collective levels – beyond corporate competition –
for we live on one planet: the only one we’ve got so far!

Is Time really Money?

Regarding time, Giordano Bruno[23] was burnt at the stake, for having said things the Catholic Church didn’t approve of, for example: “There is no time. There is only movement. For if there is no movement, there is no time.”

Regarding money, the Capitalist Church has established doctrines that are completely untenable, as interest upon interest aka compound interest grows exponentially.

Scientists understand this. The chart shows the exponent in the formula on the left, and the number of years at the bottom. Compound interest at different rates on the right doesn’t just add up or multiply. It ‘grows exponentially’.

But economists are taught all sorts of content without the creation of money from thin air, let alone the disastrous effects of its ‘growth’ as context.

Which regularly monitored data sets will bring this insight home to C-Suites across the globe? How much of your profits go to interest payments rather than real time staff?

As data scientists, we can safely say that All things financial are transactions. That means records in data bases with a sender and a recipient as source and target.

On a day-to-day basis these questions emerge:

  1. How do we select the financial data that is most significant to qualify the pressures imposed on our thinking and decision making processes?
    • what data determines the framework within which we move money from investors and clients to staff and suppliers?
    • where are credible sources other than financial markets that make money out of money as usury[24] which was already condemned by Aristotle?
    • how can we compare and rank data on a corporate and public level?
  2. Which software do we use to give it visual meaning?
    • Who’s going to adopt layering[25] of their data?
    • Who’s going to support visual comparisons of public data in the public interest?
    • Who’s going to contribute to the ‘vocabulary of metrics’?
  3. And what are the messages that we derive from our data visualisations?
    • Are we looking at short, medium and long trend periods?

I had approached Martin because it occurred to me that Corinium could provide a vehicle for not just publishing texts as references and pointers but also data and maybe even images.

For references and standards are being established by ‘industry’.

Corinium’s spectrum of leading edge thinking could lead to a ‘smart’ selection of data sets that help us as benchmarks and references, when we make financial considerations:

  1. What are average values across countries and companies of
    1. profits and losses per person – as a complementary measure to GDP;
    2. shareholder returns per person / institution – an additional metric to ROI;
  • salary rises – to compare with official figures of inflation;
  1. voluntary or enforced redundancies and replacements?
    1. with the indicator of whether they were replaced by machines and automation.
  2. what differences do we find between privately and publicly owned organisations?

Quantity vs Quality – of Jobs and other Subjects of Measuring

An example for questioning the number of jobs being replaced by machines and the resulting quality of jobs that actually has emerged is given by David Autor, Ford Professor of Economics, asking: Why are there still so many jobs?[26]

He does distinguish between human genius and creativity as “inspiration vs perspiration”.

By putting the inspiration for software and data selection together with intelligent report writing and visualisation, we can create synarchy: the joint hierarchy between human thinking and machine intelligence. That can bring about the digital changes we are hoping for.

I discovered the concept through the late visionary artist Rowena Pattee Kryder[27] who designed amazing symbols that accompany remarkable paintings describing a New Earth that is emerging from an Old Earth we are leaving behind.




The idea of achieving Synarchy as Social Harmony between gender [the issue of sex] and generations [the issue of money] relies on:

  • Individuality as ‘Source’;
  • Cooperation as ‘Agent’;
  • Technology as ‘Process’ with
  • Synarchy as ‘Effect’.

Technology thus needs to be seen as a process that has an effect on the quality of our social harmony, as it changes over time. It seems pretty obvious that we need to use our sphere of influence consciously to steer our organisations into new realms of thought, expression and communication.

Has the time come not just for conscious communication but also conscious money, as Data Scientists understand their media as messengers and information providers to make financial decisions?

The visualisation of data and information as charts or infographs is thus a new art form with which we express our insights and intelligence – derived from company-internal or open data sets – visualised in the most effective manner which is visually striking.


Avinash Metoo[28] from Mauritius talks about Knowledge 7[29] as his training organisation that adds A for Arts to STEM. He wants students to ‘learn digital’ in practical hands-on ways and thus grow Africa together. Looking at Africa, which organisation can afford not to go down ethical and socially responsible routes?

What kind of data sets with which kind of benchmarks might we agree on at Digital Roundtables[30] and in Discussion Groups to contribute to Corinium Digital[31]? Can we bring thought leadership together with conscious data and conscious metrics?

Digital is Individual and Intelligence comes from Learning by Doing

At the end of an email address is a person with different size devices – in the context of an organisation and its culture. Together, we are embedded in the economics, politics and mainstream media that influence our thinking.

Connected Thinking includes building bridges between

  • writing and using software to gather, analyse and visualise data,
  • human intelligence to interpret and attribute meaning
  • making executive decisions that affect the staff of a whole company and
  • defining conditions and criteria for automation.

Whether the effects of automation are desirable and whether we choose to implement and adopt them, is an ethical decision of our conscience:

  • what are we trying to achieve by creating or adopting AI?
    • o Do we achieve that goal with our idea?
  • what can we offer to the people we are replacing?
    • o can our conscience afford to please anonymous shareholders at the cost of redundancies?
    • o how do we engage our shareholders in our data-informed decision making processes?
  • who wants to be part of an expert roundtable to design data strategies and software solutions to make AI and ML good for society?

Who is willing to STOP the sorcerer’s apprentice who forgot the password to stop his magic? Only the Conscious Master is allowed to invoke ‘spirits’ such as autonomous robots, maybe.

May we become more knowledgeable as we learn more by seeing more data and interpreting it by visualising it in different ways. Compare and Contrast is one of the ways of visual learning. But we each have our own knowledge base and our individual ways of learning. May we continue enjoying likeminded people thanks to Corinium to connect our thinking and elevate our perspective!