In the second part of a two-part article, MAL FLETCHER, social futurist and chairman of London-based thinktank 2030Plus, looks at the important role critical thinking will play in our future data management…
London, UK
John F Kennedy said, “Too often we enjoy the comfort of opinion without the discomfort of thought.”
That, unfortunately, is all too true in our time. Data literacy programs can help us develop critical thinking skills so that we make reliable judgements based on credible information.
PICTURE: Urupong/iStockphoto
Critical thinking involves questioning the relevance and reliability of what we hear, read or see. It helps us analyse different approaches, looking at how consistent each idea is within itself and how workable it is in practice.
How helpful might that have been during the pandemic? Constant news streams about COVID-19 variants and lockdowns led to an outpouring of not-very-objective, conspiratorial thinking.
“Critical thinking will become even more important as the rate of workplace automation increases.”
Scientific figures that were barely understood by most of us were selectively pored over and interpreted by armchair experts, who formed combative camps of opinion, each flying the flag for this or that conspiracy.
Critical thinking will become even more important as the rate of workplace automation increases.
As robots become more sophisticated and their cost of manufacture drops, more low-skilled jobs will be lost to the human workforce.
But artificial intelligence will impact middle-wage jobs, too, especially those involving data collection and analysis.
In some parts of Europe, speeding offences are recorded, tickets are issued and penalties for non-payment are applied without human agency. The entire system is automated.
In time, professions will suffer. In some quarters they already are, most notably in law, where chatbots already perform pro forma functions.
Is there any reason why networked AI robots couldn’t represent people before the courts? The one sticking point might be that empathy is an important part of legal proceedings. Mitigating circumstances are often considered when it comes to deciding levels of guilt and corresponding punishments.
Empathy is built upon fellow feeling, grounded in shared human experiences. By definition, this is something a machine intelligence cannot have.
Nonetheless, AI is making its presence felt in the arts. Painting, drawing, writing and music composition are no longer purely human activities.
For human beings, all of this workplace automation will set temperatures rising. Clear heads will be vital.
Ethical questions will also arise with the synthesis of technology and human physiology, through brain implants, 3D-printed organs and advanced prosthetics. These too will require critical thinking.
Elon Musk’s Neuralink company aims to place thousands of small electrodes in the human brain, which would read signals from neurones and transmit them to remote computers. This might allow not only the analysis of health problems but new ways of regulating them.
It might enable sight-challenged people to recover their sight and recovery of function for people who’ve suffered paralysis. It might also treat conditions such as addiction, PTSD, depression and anxiety.
Neuralink says it wants to start human trials this year. But it’s not clear how much effort has been made to identify and address ethical issues, such as the line between human and machine.
This is why, in the coming days, professional ethicists will play a role similar to that of theologians and philosophers in times past.
They’ll puzzle over complex philosophical problems that have immediate real-world implications. We need to equip these thinkers now. And we need to offer people from all walks of life the chance to train in ethical and critical thinking.
Analyse, evaluate and synthesise
Data literacy courses will also focus on the analysis of information. Evaluation is a key part of critical thinking, seeking out flaws in reasoning and helping us understand the practical implications of ideas.
Critical thought involves synthesis skills, too – applying logic and reason to formulate healthy conclusions.
All of this will become increasingly vital in an age of networked machine learning. Computer networks learn not only through the application of their own programming but by referencing the coding of other machines via the cloud.
Networked ML carries huge potential opportunities and challenges. For example, on the positive side, governments may respond faster to natural disasters if networked machines can constantly update their predictive models.
The same machine networking, however, might cause fully autonomous robotic weapons to act on flawed data, while also passing their faulty conclusions to other weapons.
There are many questions waiting to be answered. They won’t be answered satisfactorily if we don’t train ourselves and emerging generations to be data literate.
Where do we start?
How can we prepare ourselves to deal with AI, machine learning and as yet unseen technological challenges? Where does data literacy training start, in practical terms?
It begins with our everyday experience of technology.
For example, we need to understand the real psychological effects produced by virtual experiences.
Much has been said about the emergence of the metaverse. Its immersive nature offers potential benefits for medicine, mental healthcare, education and much more.
Yet this nascent internet technology is already attracting perpetrators of virtual assault, including online gang assault. Attackers and their victims exist only in avatar form, but this does little to reduce the psycho-emotional impact on those who are targeted in this way.
We also need training in encryption – how it works, as well as its limitations. Encryption is built on the principle that plain text can be scrambled into coded text, which is only readable by people who possess an unscrambling key.
The whole process relies on the security of the encryption software – how resistant it is to hacking – and the safety of the encryption key – how difficult it is to steal.
In 2013, a hacker was able to bypass encryption on the bitcoin protocol and steal an estimated $US350 million worth of the cryptocurrency.
In 2019, a sophisticated attack on the encryption system of the Canadian Imperial Bank of Commerce allowed hackers to steal more than $US65 million from customers.
Both attacks were made possible by exploiting vulnerabilities in encryption systems.
Encryption is not a magic bullet, says Mal Fletcher. Yet he adds that “in the next few years, nearly every aspect of our online lives will rely on the use of encrypted data”. PICTURE: KanawatTH/iStockphoto.
Encryption is not a magic bullet. Yet in the next few years, nearly every aspect of our online lives will rely on the use of encrypted data.
Data literacy training shows us how to update our encryption measures and to ensure that those who handle our data – businesses, banks, governments and Big Tech – regularly do the same.
It also provides skills to identify cybercrimes such as identity theft and other online scams.
Identify theft involves stealing someone’s personal information, so as to access online accounts or commit fraud.
ID theft often targets the young. The US saw a 91 per cent increase in data crime victims aged 18 to 25 in the year ending early 2020, according to the Federal Trade Commission.
Another report revealed that almost half of all American adults aged 18 to 25 experienced data theft or fraud in 2020.
Research by the British banking industry found that 4.5 million fraud offences were committed in the year starting March 2020 – an increase of 25 per cent on the previous year. This was driven by a large increase in cases of advance payment fraud, using phishing scams.
Phishing involves sending messages that seem to come from legitimate sources, such as email accounts, to trick people into sending funds or giving up information. Teaching people to identify early warning signs of phishing should be on any data literacy curriculum.
Parents and guardians should be trained in how to protect the safety of their children online. This will include teaching them to ask perceptive questions about how and why they perform certain tasks online.
Childcarers need to limit the information they upload about their charges. Children will often learn more from our actions than our words. When it comes to online behaviour, what one generation tolerates, the next may well treat as normal and seek to outdo.
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Power of the technokings
Data literacy training will also enlighten people about the growing power of the technokings, the heads of Big Tech companies.
Despite their talk about using technology for altruistic purposes, the actions of technokings often reveal more of a profit-making motive. Most of their profit comes from user data.
The fact that technokings value data above all else is shown in their support for a fully cashless economy.
Our use of cashless payments has boosted data generation exponentially. We generate data about ourselves with every purchase. Data about our buying preferences, yes, but often also about where we live and our bank account details. We have little or no control over what happens to that data once we leave the store.
Does it remain with the merchant and her/his bank? Do they use it to pitch other products to us in future? Is it passed on to third parties for similar uses?
“Full cashlessness would leave millions of people facing digital debt because studies show that without cash we spend more with less forethought. It would also boost the likelihood of privacy invasion, either by unscrupulous government agencies or by cyber-criminals.”
Entering into a fully cashless economy would benefit Big Tech, banks and merchants much more than consumers. This is why some politicos and economists argue for a central bank digital currency, which would ostensibly provide the convenience of cyber-currencies without their obvious downsides.
This is naive. It isn’t simply the ownership of a currency platform but the nature of cashlessness itself that presents a problem.
Full cashlessness would leave millions of people facing digital debt because studies show that without cash we spend more with less forethought. It would also boost the likelihood of privacy invasion, either by unscrupulous government agencies or by cyber-criminals.
Big Tech’s devotion to cashlessness is a cause for concern among security agencies. In some parts of the world, Big Tech groups are closely aligned with single-party governments. Researchers have warned social media users that TikTok is linked to the Chinese government and may be part of that country’s growing espionage apparatus.
Whether or not that’s true, we should equip people to question the intentions of Big Tech – especially where the platforms we use offer us no opt-out on data collection.
This is all part of teaching data literacy. It can be done in a proactive way without producing paranoia, which always blocks curiosity and innovation.
Data science anyone?
Students at the secondary level should be taught data science, too. While data literacy looks at how we access and analyse data, data science is more technical. It teaches skills involved in coding, statistics and machine learning.
Where once subjects like physics, biology and chemistry were considered core science components, curricula should now also include data science. Without understanding it, young adults will be poorly equipped to engage in a world that’s increasingly impacted by AI and ML.
If there’s one thing the pandemic showed us, it is the vital importance of medical professionals, researchers and statisticians. These people are skilled in STEM-related fields – in science, technology, education and maths. We will need more of them going forward.
In parts of the UK, which has a relatively good record in STEM education overall, up to 40 per cent of jobs in some STEM-related fields can’t be filled. There are not enough qualified applicants.
This does not mean that we should skimp on teaching the arts. As well as producing works that challenge our minds and enrich our souls, arts training provides skills that are indispensable to all forms of innovation.
Our trust in data and its many uses is a key currency in today’s world. It will play an even greater role in our future. Data will shape so many more of our experiences and interactions. We will need to become data literate.
Mal Fletcher is a social futurist, social commentator and speaker and the chairman of 2030Plus, a London-based thinktank. He has researched global social trends for more than 25 years and speaks to civic leaders worldwide about issues relating to socio-cultural ethics & values, PESTLE Analysis, civic leadership, emerging and future technologies, social media, generational change and innovation. First published at 2030Plus.com. Copyright Mal Fletcher, 2023.
Mal Fletcher is a member of the Sight Advisory Board.
