Torn between profit and sustainability
What do activist investors stand for ¬– and what can we expect as they reach British shores?
The first activist investors, as with several other financial innovations of the past few decades, sprang up in the US. Although their shift in priorities towards ESG goals has recently pushed them into the limelight, they have been around since at least the 1980s.
The tactics of activist investors or – as they’re also called – shareholder activists is reminiscent of hostile takeovers in terms of aggressiveness and outcomes. Where they differ, though, is that they can get CEOs ousted, companies broken up and severed arms of the organisation sold without gaining a majority stake in the targeted company.
Activists come in two shapes and sizes
Most activist investors are asset managers investing the funds of large asset owners such as pension funds, endowments and foundations, while hedge funds – actively managed investment pools – play a secondary but equally key role.
With trillions of dollars under their management, leading asset managers can bring about step changes in a relatively short time, enabling them to make a difference on a global scale. Larry Fink, the CEO of BlackRock – the world’s biggest investment management company – is a staunch supporter of ESG investment that aims to make a positive impact on climate change, working conditions or the diversity of boards in general.
In Fink’s case, a positive stance on impact investments means that trillions of dollars will stand a good chance of ending up in renewable energy generation and storage or carbon capture projects.
Nevertheless, if BlackRock’s CEO doesn’t believe in divestment from fossil fuels, which happens to be the case, then the company will doggedly leave some billions of dollars in assets connected to coal.
Torn between short- and long-termism
Opinions vary regarding whether the appearance of activist investors on the corporate horizon is a boon or a curse. Studies have shown that the financial performance of companies knocked into shape by their shareholder activists will improve during the 24 months following intervention, but there is no evidence for any long-lasting positive effect beyond that.
Thanks to their balancing act between profits and sustainability, activist investors have been condemned by environmentalists and corporate leaders with traditional profit-first perspectives.
While their mission is mainly to inject ESG-driven long-termism into the minds of CEOs and board members blinkered by short-term profits, sometimes they can also undermine the noblest sustainability efforts that don’t bring about immediate results.
Criticism that he was more interested in saving the planet than saving the firm was levelled at Emmanuel Faber, who was CEO and Chairman of Danone until he was ousted by small shareholder activists. Faber went on to serve as the Chair of the International Sustainability Standards Board, set up last November.
In the UK, Unilever, an acclaimed pioneer of net-zero emissions battered by overambitious acquisition plans, saw the price of its consistently underperforming shares rise by 6 per cent in January when news broke that Elliott Management, an activist hedge fund, had built a stake in it.
A 2020 study also suggests that those who have sleepless nights dreading sustainability supplanting profits as the top priority have as yet no cause for great concern. While believers of top-down change may see the current popularity of SDG investments as the long-term benefit of the Principles of Responsible Investment – the 15-year-old UN initiative – the study has found otherwise. Asset managers who signed on to the United Nations principles did not on average improve the social and environmental performance of their investments and “overall, a reasonable reader may perceive [the study’s] findings as consistent with PRI funds’ greenwashing.”
The study also points out participants’ fervour to widely advertise their PRI affiliation on company websites, marketing materials and fund documents, which is a sign of an attempt to maximise short-term profits rather than being held hostage to long-term investment horizons.
Activist investors on this side of the pond
In response to low UK share prices, US activist investors have set their sights on a couple of UK conglomerates that have been underperforming for some time – GSK, a targeted pharmaceutical company, for example, has fallen from third to 11th place by revenue in two decades.
Compared to the US, the UK’s corporate legislative framework is more empowering for shareholders to promulgate their views among members of the board and become drivers of strategic change. There is also less state and family ownership in public companies that could stand in the way of shareholder activists’ shake-up plans.
To accommodate this new, more conducive environment, activist investors eyeing UK companies seem to have given up on the hardball they play in the US. However, a somewhat softer tone and less public attacks against CEOs in the media doesn’t mean we won’t see boards and activist investors lock horns on British soil.
On the upside, what we can also expect is the improving performance and share prices of British public companies that, in a best-case scenario, also have ESGs incorporated into their growth strategy.
Zita Goldman
There are challenges but also potential benefits of digital distractions
We are in the midst of a battle for our attention. Our devices have hijacked our brains and destroyed our collective ability to concentrate – to the extent that we’re even seeing the emergence of a “goldfish generation”. That, at least, is the story that’s increasingly being told. But should we be paying attention to it?
Journalist Johann Hari’s new book, Stolen Focus, has just joined a chorus of voices lamenting the attention crisis of the digital age. His and other recent books reflect, and perhaps fuel, a public perception that our focus is under attack.
Indeed, in new research by the Policy Institute and Centre for Attention Studies at King’s College London, we found some clear concerns.
Faced with the kinds of findings that arose from our research, it is easy to be nostalgic about a past that existed before the digital revolution. But new technologies have been blamed for causing crises of distraction long before the digital age, so how should we respond to the current challenges?
An attention crisis?
We surveyed a nationally representative sample of 2,093 UK adults in September 2021, asking about their perceptions of their attention spans, their beliefs in various claims about our ability to focus, and how they use technology today.
Half of those surveyed felt their attention spans were shorter than they used to be, compared with a quarter who didn’t. And three-quarters of participants agreed we’re living through a time where there’s non-stop competition for our attention from a variety of media channels and information outlets.
The distraction caused by mobile phones in particular appeared to be a real issue. Half of those surveyed admitted they couldn’t stop checking their phones when they should be focusing on other things – and this wasn’t just an issue for the young. Despite the generational stereotypes of teenagers glued to their screens, a majority of middle-aged people said they struggle with this too.
And although many recognised that they spent a lot of time on their phones, they still hugely underestimated just how much. The public’s average guess was that they checked their phones 25 times a day but according to previous research, the reality is more likely somewhere between 49 and 80 times a day.
There has long been a worry about the threat to attention brought by new cultural forms, whether that’s social media or the cheap paperback sensation novels of the 19th century. Even as far back as ancient Greece, Socrates lamented that the written word creates “forgetfulness in our souls”. There has always been a tendency to fear the effects new media and technologies will have on our minds.
The reality is we simply don’t have the long-term studies that tell us whether our collective attention span has actually shrunk. What we do know from our study is that people overestimate some of the problems. For example, half of those surveyed wrongly believed the thoroughly debunked claim that the average attention span among adults today is just eight seconds, supposedly worse than that of a goldfish. There’s not really any such thing as an average attention span. Our ability to focus varies hugely depending on the individual and the task at hand.
Attention snacking
It’s also important to not overlook the many benefits that technology brings to how we live. Much of the public surveyed recognised these, so while half thought big tech and social media were ruining young people’s attention spans, roughly another half felt that being easily distracted was more to do with people’s personalities than any negative influence that technology may or may not have.
That aside, is "dispersed” attention always a bad thing?
Two-thirds of the public in our study believed switching focus between different media and devices harms our ability to complete simple tasks – a belief confirmed by psychological studies. Intriguingly, half of the public also believed multi-tasking at work, switching frequently between email, phone calls, or other tasks, can create a more efficient and satisfactory work experience.
So what if we explore the benefits of distraction as well as the negative impacts? Might we find a more balanced picture in which distraction is not always in and of itself a bad thing, but a problem in certain contexts and productive in others? In other words, what if those lamenting a crisis in attention are not wrong, but only represent part of the picture?
For all the challenges we experience in having our attention toggle between tasks, in some scenarios, this might help refresh the mind, keep us alert, and stimulate brain connections and creativity. Unified attention may be an ideal, but it may not always be a realistic good for the type of animal that we humans are.
We hear about the benefits for the body of “exercise snacking” or circuit training, so perhaps we need to ask how we might harness the potential benefits for the mind of “attention snacking”. The brain is, after all, a physical organ.
There is no question that we need to figure out how to live better with the “attention economy”, and that the monetisation of our attention is challenging us in fundamental ways. However, our electronic gadgets are not going away and we need to learn how to harness them (and the distractions they pose) for individual and social good.
Our attention has always been the only real currency we have, and for that reason, it has always been fought over; this is not a new problem, but in the digital age it is taking new forms. We need a better response to this situation – one that understands the risks but is also bolder in asking questions about the opportunities.
Marion Thain, Dean of the Faculty of Arts and Humanities, King's College London
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Social media: a force for good in the fight against hate around the world
Critics sometimes label social media as a malign phenomenon, a place where bullying, extremism and crime are given a free rein to thrive, and bad actors are allowed to hide behind a veil of anonymity. As the Muslim World League marks the year anniversary of its #RejectHate campaign, however, its Secretary General, Mohammad Abdulkarim Alissa, explains how online platforms are proving to be a force for good globally.
With nearly 98 per cent of the population online, Saudi Arabia is one of the most digitally connected societies in the world. Similarly, however, every country’s cyberspace has the potential to become an echo chamber of fundamentalist rhetoric if left unchecked. With this in mind, according to the Muslim World League (MWL), a Mecca-based NGO that promotes moderate and peaceful Islamic vales, good is winning over evil in the online world.
Since Alissa became Secretary General of the MWL, the NGO has done much to combat extremism, hatred, injustice and oppression both within and towards the international community. In 2019, the organisation was responsible to the conception of the Charter of Makkah, which saw Muslim leaders from 139 countries agree on 30 key principle points of modern Islam, including the need for equality, religious harmony and female empowerment. Most recently in March last year, MWL launched the #RejectHate campaign, inviting supporters to sign an online petition urging social media companies to do more to combat bigotry and anti-Islamic sentiment online.
According to the campaign’s Change.org page, one in every thousand posts from one major social network violates the company’s rules on hate speech but more than three-quarters of this content is allowed to remain on the platform, even after it’s been reported and investigated. “Muslims continue to suffer personal abuse, threats, and physical violence fuelled by content spread through social media,” the webpage reads. “Now is the time for [these networks] to impose a zero-tolerance policy towards hate speech targeting any religion. These companies must introduce more robust procedures to see it quickly removed.”
But while pushing for social media companies to take more responsibility for the content on their platforms, Alissa, a Saudi religion leader and the Secretary General of the MWL, says the #RejectHate campaign and other educational tools are ensuring the social media platforms billions rely on are doing more good than harm across the world. “Extremists and terrorism have benefited from social networking sites, yes,” he admits, “but powerful voices in the worlds of religion and thought leadership are now active themselves online in ways which limit the likelihood of unfounded speech dominating the conversation.”
He credits social media with having brought people from all walks of life, closer together, removing the barriers of distance while dispelling myths and facilitating important conversations between neighbouring but diverse communities. He believes social networks have also empowered the people of the region to become more discerning with their media consumption, allowing access to raw, unfiltered data and marginalised voices. “Innovation in offering users ready access to candid dialogue, relevant local networks, the ability to fact check and other personalised connections have not only worked to benefit society but, in many ways, reorder its ability to communicate with itself,” says Alissa.
The other edge of that sword, however, is when online communities blindly stick within their own belief systems and narratives, creating online echo chambers that breed negativity and dangerous ideas. “Once the conversation is tainted with hate speech and general negativity, society suffers the result,” says Alissa.
While he supports regulations that would see social media platforms act as stewards for the information on their platforms, the Secretary General is staunchly against ironclad censorship, saying such an approach would go against the very lifeblood of social media – its openness. He is instead calling for more education and thought leadership campaigns to follow in the footsteps of #RejectHate.
“By strengthening the manner in which society engages with social media via public awareness campaigns, a continued adherence to high moral values will prevail,” he hopes. “Hate speech and extremist hate are outliers within the wider world of social media engagement, a truth which our awareness campaign has sought to leverage in offering a continued optimism for healthy engagement.”
While the protection against overuse and the stamping out of misuse have never been more important, we must not let these dark spots eclipse the light of social media’s great potential, says Alissa. “I don’t think those blemishes outweigh the benefits of social media, nor are they obstacles that can’t be overcome.”
Written by Crystal Reid
INDUSTRY VIEW BY THE MUSLIM WORLD LEAGUE
Humans v AI: here’s who’s better at making money in financial markets
Artificial intelligence (AI) has now closely matched or even surpassed humans in what were previously considered unattainable areas. These include chess, arcade games, Go, self-driving cars, protein folding and much more. This rapid technological progress has also had a huge impact on the financial services industry. More and more CEOs in the sector declare (explicitly or implicitly) that they run “technology companies with a banking license”.
There is also a rapid emergence and growth of the financial technology industry (fintech), where technology startups increasingly challenge established financial institutions in areas such as retail banking, pensions or personal investments. As such, AI often appears in behind-the-scenes processes such as cybersecurity, anti-money laundering, know-your-client checks or chatbots.
Among so many successful cases, one seems conspicuously absent: AI making money in financial markets. While simple algorithms are commonly used by traders, machine learning or AI algorithms are far less usual in investment decision-making. But as machine learning is based on analysing huge data sets and finding patterns in them, and financial markets generating enormous amounts of data, it would seem an obvious match. In a new study, published in the International Journal of Data Science and Analytics, we have shed some light on whether AI is any better than humans at making money.
Some specialist investment companies called quant (which stands for ‘quantative’) hedge funds declare that they employ AI in their investment decision-making process. However, they do not release official performance information. Also, despite some of them managing billions of dollars, they remain niche and small relative to the size of the larger investment industry.
On the other hand, academic research has repeatedly reported highly accurate financial forecasts based on machine-learning algorithms. These could in theory translate into highly successful mainstream investment strategies for the financial industry. And yet, that doens’t seem to be happening.
What is the reason for this discrepancy? Is it entrenched manager culture, or is it something related to practicalities of real-world investing?
AI’s financial forecasts
We analysed 27 peer-reviewed studies by academic researchers published between 2000 and 2018. These describe different kinds of stock market forecasting experiments using machine-learning algorithms. We wanted to determine whether these forecasting techniques could be replicated in the real world.
Our immediate observation was that most of the experiments ran multiple versions (in extreme cases, up to hundreds) of their investment model in parallel. In almost all the cases, the authors presented their highest-performing model as the primary product of their experiment – meaning the best result was cherry-picked and all the sub-optimal results were ignored. This approach would not work in real-world investment management, where any given strategy can be executed only once, and its result is unambiguous profit or loss – there is no undoing of results.
Running multiple variants, and then presenting the most successful one as representative, would be misleading in the finance sector and possibly regarded as illegal. For example, if we run three variants of the same strategy, with one losing -40 per cent, the other one losing -20 per cent, and the third one gaining 20 per cent, and then only showcase the 20 per cent gain, clearly this single result misrepresents the performance of the fund. Just one version of an algorithm should be tested, which would be representative of a real-world investment setup and therefore more realistic.
Models in the papers we reviewed achieved a very high level of accuracy, about 95 per cent – a mark of tremendous success in many areas of life. But in market forecasting, if an algorithm is wrong 5 per cent of the time, it could still be a real problem. It may be catastrophically wrong rather than marginally wrong – not only wiping out the profit, but the entire underlying capital.
We also noted that most AI algorithms appeared to be “black boxes”, with no transparency on how they worked. In the real world, this isn’t likely to inspire investors’ confidence. It is also likely to be an issue from a regulatory perspective. What’s more, most experiments did not account for trading costs. Though these have been decreasing for years, they’re not zero, and could make the difference between profit and loss.
None of the experiments we looked at gave any consideration to current financial regulations, such as the EU legal directive MIFID II or business ethics. The experiments themselves did not engage in any unethical activities – they did not seek to manipulate the market – but they lacked a design feature explicitly ensuring that they were ethical. In our view, machine learning and AI algorithms in investment decision-making should observe two sets of ethical standards: making the AI ethical per se, and making investment decision-making ethical, factoring in environmental, social and governance considerations. This would stop the AI from investing in companies that may harm society, for example.
All this means that the AIs described in the academic experiments were unfeasible in the real world of financial industry.
Are humans better?
We also wanted to compare the AI’s achievements with those of human investment professionals. If AI could invest as well as or better than humans, then that could herald a huge reduction in jobs.
We discovered that the handful of AI-powered funds whose performance data were disclosed on publicly available market data sources generally underperformed in the market. As such, we concluded that there is currently a very strong case in favour of human analysts and managers. Despite all their imperfections, empirical evidence strongly suggests humans are currently ahead of AI. This may be partly because of the efficient mental shortcuts humans take when we have to make rapid decisions under uncertainty.
In the future, this may change, but we still need evidence before switching to AI. And in the immediate future, we believe that, instead of pinning humans against AI, we should combine the two. This would mean embedding AI in decision-support and analytical tools, but leaving the ultimate investment decision to a human team.
Barbara Jacquelyn Sahakian, Professor of Clinical Neuropsychology, University of Cambridge; Fabio Cuzzolin, Professor of Artificial Intelligence, Oxford Brookes University, and Wojtek Buczynski, PhD candidate / consultant, University of Cambridge
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Empowering enterprise digital transformation
Digital transformation is one of the most critical priorities for many organisations today. However, a lot of businesses struggle to make the necessary changes to keep up with the competition. Businesses need to focus on three key areas – culture, technology and structure – to empower digital transformation.
Creating digital culture
The first step is to create a culture that is open to change and innovation. A digital culture is one that encourages employees to be creative and experiment with new ideas. It also means establishing clear goals and expectations and support employees in their efforts.
What are the hallmarks of digital culture?
- Employees are encouraged to be creative and experiment with new ideas
- There is a focus on collaboration and teamwork
- The organisation is willing to take risks
- The culture is open to change and innovation
- Employees are given the resources they need to be successful
How can organisations empower a digital culture?
The key is to provide the necessary resources and support to employees. This support includes training, mentorship and access to technology and tools. It’s also important to create a positive environment that encourages risk-taking and innovation.
Enabling enterprise digital transformation
Once the culture is in place, businesses need to focus on the technology solutions that will enable them to succeed. This step includes choosing the right tools and platforms and ensuring they are integrated with the rest of the organisation. It also means developing a robust digital strategy and roadmap aligned with the overall business strategy.
This includes adopting new technologies and platforms and redesigning processes to make them more efficient.
What are some of the challenges with enterprise digital transformation?
- Adopting new technologies and platforms
- Redesigning processes to make them more efficient
- Integrating new systems with legacy systems
- Building the infrastructure that is agile and able to respond quickly to changes
Technology solutions
What are some key considerations when choosing technology solutions?
- The solution needs to be compatible with the rest of the organisation
- It needs to be scalable so that it can grow with the business
- It must be secure and compliant with regulations
- The solution should be easy to use and intuitive
- There should be a clear plan for implementation and support
Structuring for success
The final step is to ensure that the organisation is structured for success. This includes creating the right teams and appointing the right leaders. It also means defining clear roles and responsibilities and establishing processes and protocols.
What are some of the challenges with structuring for success?
- Defining clear roles and responsibilities
- Establishing processes and protocols
- Creating the right teams and appointing the right leaders
- Ensuring that the organisation is agile and can respond quickly to changes
- Developing a governance model that outlines how decisions will be made and how resources will be allocated
Challenges to enterprise digital transformation
No-code technologies are becoming increasingly important as businesses strive to become more agile and responsive. These technologies allow businesses to create applications without the need for coding expertise. This makes it easier for non-technical employees to get involved in the development process and helps to speed up the deployment process.
No-code tools boost all three pillars of digital transformation: culture, technology, and structure. They make it easier for businesses to adopt new technologies, redesign processes and collaborate across teams.
How can businesses take advantage of no-code technologies?
- Evaluate your needs and identify the right tool for the job
- Invest in training and education so employees can learn how to use the tool
- Don’t be afraid to experiment: try out different tools and see what works best for your business
- Empower employees to use the tool to get them involved in the transformation process
What lies ahead?
Businesses need to invest in the right tools and platforms, develop a robust digital strategy and roadmap, and structure success. Enterprise digital transformation will move towards:
- A focus from people to technology
- Businesses becoming more agile and responsive
- An increase in the use of no-code technologies
- A growing importance of data
- A greater focus on the customer experience
To find out more, get in touch with EasySend.
Tal Daskal is the CEO and co-founder at EasySend. Tal is an expert on all things digital transformation in banking and insurance and is a passionate advocate for the paradigm shift towards no-code application development in the financial sector.
INDUSTRY VIEW FROM EASYSEND
UK businesses reap the benefits of remote hiring
The past two years have seen an exodus of talent from the UK. That has stung companies needing to recruit, but it has also pushed many to look farther afield for employees and improve their international talent-hiring capabilities now they no longer need to be constrained to the UK.
The changes to the job market in the UK brought about by Brexit and COVID-19 have been substantial. The number of EU citizens seeking work in the UK since Brexit has fallen by 36 per cent since 2019, while 70 per cent of UK companies surveyed by the British Chambers of Commerce said they have faced problems recruiting. The problem is particularly acute in the UK’s tech sector, where cybersecurity, big data and data architecture are all experiencing major shortages of talent.
“Business leaders are realising that they need to look outside of the usual channels to find great new talent,” says Nadia Vatalidis, VP of People at Remote, which has carved out a specialism in helping employers hire overseas. “A core part of this is the realisation that employment doesn’t need to be restricted to geographical location, and hiring strategies can be evolved to be much more inclusive. Fortunately, the tech sector is perfectly suited to remote work.”
Looking further afield
At first glance, the process of hiring overseas talent looks burdensome, with companies forced to contend with a range of local labour laws that can slow and complicate the acquisition process. There are substantial fees involved, with companies required to register local legal entities. They must determine how best to secure efficient cross-border payroll and be sure that the status they give to employees – whether employed, self-employed or otherwise – aligns with the local taxes they pay. They also need to navigate the different languages of each of the countries they hire in.
However, there are options to make the entire process straightforward and efficient.
UK companies are increasingly looking to employers of record (EORs) to enable remote hires. These third-party organisations act as go-betweens for a client and a local employee, taking care of background checks on candidates, the drawing up of contracts, filing taxes and many other functions that a company without a local footprint needs to carry out.
In short, it acts as a local employer – and a good EOR will save a company significant money, as well as ensure it avoids the risks that can come with recruiting talent outside of its own borders.
“Employers can now find talent so much faster than before,” Vatalidis says. “By removing geographic barriers to hiring, a huge international talent pool opens up, creating opportunities for talented people wherever they are in the world.”
There’s also the matter of local knowledge. Even something as seemingly straightforward as benefits that workers should receive in each country could prove to be a stumbling block if not approached carefully. Health insurance is one example. If the scenario were to be flipped and an overseas company were to hire a UK citizen, there would be no need to consider health insurance for that person. But if a UK company were to hire someone in the US, where state-provided healthcare is minimal, then health insurance would more than likely be an expectation. Further afield – for example, in India – there might be the additional matter of a remote employee expecting that the health insurance package they’re offered includes cover for their parents.
Local knowledge is therefore vital, and a strong EOR can help to illuminate how social norms and expectations influence the decisions a candidate makes about which company they choose to work for.
Taking the headaches away
But how does a company know which EOR to go with? And how can it gain a better understanding of the complex processes involved in overseas hiring?
Remote has a saying: “Think global and act local.” Long before the pandemic atomised the global workforce, it was busy developing extensive open-access resources for companies, both UK-based and international, who were looking overseas for talent. Covering topics ranging from tax and compliance to data security and global payroll – and including a country explorer page that highlights key information for each country – its output has continually emphasised the need to understand local issues.
“Businesses seeking to hire distributed teams must consider local nuances and expectations across different markets and ensure they meet local standards,” Vatalidis says. “We offer customers this level of local support to ensure salaries and working hours are in line with what is typical for that market. If these do not match, we cannot hire the employee, and businesses simply won’t be able to attract the employee to begin with.”
Remote has designed one of the most sophisticated and wide-ranging EOR models on offer. With it, UK companies can connect with local entities whose skill in managing the range of HR administrative work required has been carefully vetted.
If homegrown talent is in short supply and companies have little choice but to look overseas, developing efficient and effective processes for hiring remote workers could be the thing that ensures their survival.
“Talent is distributed all over the world, and in a completely digital work environment, there is no longer a need for companies to restrict themselves to recruiting only local candidates,” says Vatalidis.
“Hiring distributed teams provides businesses with endless opportunities, while also allowing employees an opportunity to live the life they want, where they want.”
INDUSTRY VIEW BY REMOTE EUROPE
Effective cybersecurity is the cornerstone of modern hyperconnectivity
Organisations should concentrate on the details – starting with good password management
The modern digital economy is evolving quickly. With the rise of online shopping, challenger banks and fintech innovation, as well as the likes of cryptocurrency and blockchain, new transformative technologies are rapidly changing the way organisations do business and how consumers make everyday payments. Of course, some recent developments have been accelerated by the financial services industry, where these technologies present a future of a frictionless digital economy. However, such an economy relies on increased hyperconnectivity and exposes users to a whole new range of threats, from potential ransomware to phishing scams to ‘shady’ transactions. With an increasingly digital economy, cybersecurity will of course become ever more important. As revealed by the Cyber Security Breaches Survey 2020, the frequency and sophistication of cybercrime is rising steadily year on year. Almost half of businesses (46 per cent) and a quarter of charities (26 per cent) reported cybersecurity breaches or attacks in the past 12 months. Those reporting cyber incidents are also experiencing more frequent attacks this year, with some being targeted at least once a week. To deliver a safe digital economy, consumers and businesses must ensure they are fully cyber-secure, starting with the basics and everyday authentication.
Passwords remain the de facto mechanism for authentication. However, the problem with passwords is that when they are leaked or captured by a third party, they can be used to gain unauthorised access to an account or system. This has driven many organisations to add an additional layer of security or authentication. Many sites, for example, now ask users to associate a mobile phone number with their account. The premise is that two-factor authentication does not allow anyone to log in to an associated account without access to the phone and the updated password. This should in theory prevent any third party from hijacking that account as they do not have the registered phone that generates a code to log in.
It is possible that biometric authentication will become the standard form of providing credentials in the future, although it should be combined with multi-factor methods. Many smartphones already have biometric readers or sensors incorporated into their hardware and the full deployment of interoperable biometric solutions should significantly reduce identity theft, benefitting the economy greatly with more reliable authentication solutions. That being said, while there are numerous biometric solutions, none can be considered a silver bullet and one size certainly does not fit all. The accuracy of facial recognition varies greatly due to factors such as lighting, angle and camera sensitivity. Likewise, fingerprint readers are affected by temperature and other factors and are not necessarily a ‘hackproof’ solution, as we leave fingerprints that can easily be copied on every surface. When fingerprints are scanned the finger is flat and will therefore be different when it is misaligned, wet or dirty, leading to issues when signing in with two-factor authentication. There are, of course, hardware security keys that are excellent for protecting accounts – however, hardware security tokens involve additional costs for the device and require users to carry the token on their person, proving cumbersome.
Voice recognition is becoming another viable biometric technique for authentication. However, it must be measured against both the ambient background, such as when speaking in a bar, on a train, on a street or at a sports arena. There has not been much movement in trying to implement voice authentication, but it does play a part in some multi-factor systems. The main barrier to any widespread adoption has been the problem of aural eavesdropping. This is where casual or malicious bystanders may overhear private information spoken by screen readers or users.
The objective of biometric identity authentication is to establish a bond of trust between a system and the user who is requesting system access. More specifically, identity authentication ascertains a level of trust regarding who the user claims to be. It follows that the more accurate the chosen authentication method the user can present to prove their identity, the stronger this bond of trust becomes.
To conclude, while biometric, authenticator apps or hardware token solutions may not provide us with the complete authentication solution businesses and consumers need to more fully secure their accounts and systems, they will play an increasingly important role in the future. Until some superior mechanism is created, proper multi-factor authentication via hardware security keys is the gold standard and will offer a strong line of defence.
Kevin Curran is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and Professor of Cyber Security at Ulster University. To find out more on the rise of cybercrime, visit the National Crime Agency.
Kevin Curran is a Professor of Cyber Security, Executive Co-Director of the Legal Innovation Centre and group leader for the Cyber Security and Web Technologies Research Group at Ulster University. His achievements include winning and managing UK & European Framework projects and Technology Transfer Schemes; however, he has also made significant contributions to advancing the knowledge and understanding of computer networking and systems, evidenced by more than 800 published works.
Previously the founding Editor in Chief of the International Journal of Ambient Computing and Intelligence, Kevin was the recipient of an Engineering and Technology Board Visiting Lectureship for Exceptional Engineers. He has also served as an adviser to the British Computer Society in regard to the computer industry standards and is a member of the BCS and IEEE Technology Specialist Groups and various other professional bodies.
Artificial intelligence can discriminate on the basis of race and gender, and also age
We have accepted the use of artificial intelligence (AI) in complex processes — from health care to our daily use of social media — often without critical investigation, until it is too late. The use of AI is inescapable in our modern society, and it may perpetuate discrimination without its users being aware of any prejudice. When health-care providers rely on biased technology, there are real and harmful impacts.
This became clear recently when a study showed that pulse oximeters — which measure the amount of oxygen in the blood and have been an essential tool for clinical management of Covid-19 — are less accurate on people with darker skin than lighter skin. The findings resulted in a sweeping racial bias review now underway, in an attempt to create international standards for testing medical devices.
There are examples in health care, business, government and everyday life where biased algorithms have led to problems, like sexist searches and racist predictions of an offender’s likelihood of re-offending.
AI is often assumed to be more objective than humans. In reality, however, AI algorithms make decisions based on human-annotated data, which can be biased and exclusionary. Current research on bias in AI focuses mainly on gender and race. But what about age-related bias — can AI be ageist?
Ageist technologies?
In 2021, the World Health Organization released a global report on aging, which called for urgent action to combat ageism because of its widespread impacts on health and well-being.
Ageism is defined as “a process of systematic stereotyping of and discrimination against people because they are old.” It can be explicit or implicit, and can take the form of negative attitudes, discriminatory activities, or institutional practices.
The pervasiveness of ageism has been brought to the forefront throughout the Covid-19 pandemic. Older adults have been labelled as “burdens to societies,” and in some jurisdictions, age has been used as the sole criterion for lifesaving treatments.
Digital ageism exists when age-based bias and discrimination are created or supported by technology. A recent report indicates that a “digital world” of more than 2.5 quintillion bytes of data is produced each day. Yet even though older adults are using technology in greater numbers — and benefiting from that use — they continue to be the age cohort least likely to have access to a computer and the internet.
Digital ageism can arise when ageist attitudes influence technology design, or when ageism makes it more difficult for older adults to access and enjoy the full benefits of digital technologies.
Cycles of injustice
There are several intertwined cycles of injustice where technological, individual and social biases interact to produce, reinforce and contribute to digital ageism.
Barriers to technological access can exclude older adults from the research, design and development process of digital technologies. Their absence in technology design and development may also be rationalized with the ageist belief that older adults are incapable of using technology. As such, older adults and their perspectives are rarely involved in the development of AI and related policies, funding and support services.
The unique experiences and needs of older adults are overlooked, despite age being a more powerful predictor of technology use than other demographic characteristics including race and gender.
AI is trained by data, and the absence of older adults could reproduce or even amplify the above ageist assumptions in its output. Many AI technologies are focused on a stereotypical image of an older adult in poor health — a narrow segment of the population that ignores healthy aging. This creates a negative feedback loop that not only discourages older adults from using AI, but also results in further data loss from these demographics that would improve AI accuracy.
Even when older adults are included in large datasets, they are often grouped according to arbitrary divisions by developers. For example, older adults may be defined as everyone aged 50 and older, despite younger age cohorts being divided into narrower age ranges. As a result, older adults and their needs can become invisible to AI systems.
In this way, AI systems reinforce inequality and magnify societal exclusion for sections of the population, creating a “digital underclass” primarily made up of older, poor, racialized and marginalized groups.
Addressing digital ageism
We must understand the risks and harms associated with age-related biases as more older adults turn to technology.
The first step is for researchers and developers to acknowledge the existence of digital ageism alongside other forms of algorithmic biases, such as racism and sexism. They need to direct efforts towards identifying and measuring it. The next step is to develop safeguards for AI systems to mitigate ageist outcomes.
There is currently very little training, auditing or oversight of AI-driven activities from a regulatory or legal perspective. For instance, Canada’s current AI regulatory regime is sorely lacking.
This presents a challenge, but also an opportunity to include ageism alongside other forms of biases and discrimination in need of excision. To combat digital ageism, older adults must be included in a meaningful and collaborative way in designing new technologies.
With bias in AI now recognized as a critical problem in need of urgent action, it is time to consider the experience of digital ageism for older adults, and understand how growing old in an increasingly digital world may reinforce social inequalities, exclusion and marginalization.
Charlene Chu, Assistant Professor, the Lawrence S. Bloomberg Faculty of Nursing, University of Toronto; Kathleen Leslie, Assistant Professor in the Faculty of Health Disciplines, Athabasca University; Rune Nyrup, Senior research fellow, History and Philosophy of Science, University of Cambridge, and Shehroz Khan, Assistant Professor (Status), Institute of Biomaterials & Biomedical Engineering, University of Toronto
This article is republished from The Conversation under a Creative Commons license. Read the original article.