A-E - Ethics
One of the most striking findings in PwC’s 22nd Annual Global CEO Survey is that the ‘information gap’ — the gap between the data CEOs need and what...
Making good decisions: building trust in a
The ethics of new technology and how to act
Setting the context: digital trust
The digital age presents threats and opportunities. New technologies are disrupting business models. Businesses throughout the world have access to similar resources, they use similar systems (including automation). Empowered consumers cause standards and pricing to converge. This means that intangibles play a critical role that can allow a business to differentiate and gain competitive advantage.
The first intangible on which others are built is the quality of decision-making. Management accounting is the professional discipline that informs and guides decision-making and performance management. Agility in decision-making enables businesses to adapt. And good decisions build trust.
Naturally, it’s important for finance professionals to be digitally agile — but they must also be aware of the ethical implications of new disruptive technologies. These range from the potential of bias in artificial intelligence (AI) to data’s impact on personal privacy and the effect of automation on tasks.
Failure to address ethical risks holds significant risks for a business, including reputational damage, loss of customer loyalty, declining sales and profitability, regulatory investigation, liability risk and the loss of trust.
accountants can help
Management accountants’ wide remit gives them an important role in this area.
While all directors share fiduciary responsibility, the CFO normally takes the lead in ensuring the business is managed compliantly in the interests of its investors.
Management accountants report to CFOs and cascade their influence throughout the business. This gives them a better overview than those in other disciplines. They also bring professional objectivity and awareness of public responsibilities to decision-making and performance management.
Stewardship has long been regarded as an important aspect of the accountant’s role, both in terms of risk management and ensuring that decisions are taken, and the business is managed in line with stakeholders’ interests.
This has direct benefits for the organisation. Ethics and good corporate citizenship provide opportunities for differentiation, helping it build trust in the business and its brands and so ensuring sustainable success for the business.
"Failure to address ethical risks holds significant risks for a business, including reputational damage, loss of customer loyalty, declining sales and profitability, regulatory investigation, liability risk and the loss of trust."
What is your current role and are you confident you can address ethical risks in a digital environment?
- CFO/VP/director/controller — Confident
- CFO/VP/director/controller — I need development on new practices
- Business partner/finance manager — Confident
- Business partner/finance manager — I need development on new practices
- Finance professional (non-management) — Confident
- Finance professional (non-management) — I need development on new practices.
Bias in automated decision-making
Facing up to ethical complexity
If ethics seems complex now, there’s much more to come. Thanks to cognitive computing — covering artificial intelligence (AI), machine learning, intelligent automation, natural language processing, neural networks, deep learning and more — machines may soon be making qualitative judgements. But right now, the main role of cognitive computing is to augment human intelligence.
Humans or machines in control
With traditional AI, a machine is programmed to explore vast amounts of data to find insights about causality, correlations and other complex relationships that can be expressed as an algorithm. Humans then interpret the findings and determine what action to take. So, people retain control.
With machine learning, a computer is given data on inputs, activities and outcomes, then told to analyse it to ‘learn’ how to improve outcomes.
Intelligent automation is where the machine takes control, putting the algorithms it has learned into practice and continuing to hone them based on outcomes.
Deloitte identifies the ethical risks relating to AI and machine learning as:i
- Bias and discrimination
- Lack of transparency
- Erosion of privacy
- Poor accountability
- Workforce displacement and transitions
Revealing unconscious bias
General Data Protection Regulations (GDPR) is the data protection and privacy regulation in the EU. It came into effect in May 2018 and can lead to fines of up to 4% of global turnover for abusing or failing to take care of customer data .ii
Machine learning improves the accuracy of algorithms’ predictions by weighting the variables that most influence accuracy. To check for potential bias, it’s necessary to understand which of an algorithm’s variables are most influential. What is your current role and are you confident you can address ethical risks in a digital environment?
If the data was about past applications for jobs or loans, for example, it’s possible that the machine will replicate or exaggerate any bias learned from past decision-making by humans. Such sub-optimal decision-making is not to the benefit of the business and it can be unfair to customers or employees. This was recognised over 30 years ago by the UK’s Commission for Racial Equality when a program, used to select applicants for interview by a British medical school,iii was found to discriminate against people with non-European names. It achieved 90–95% accuracy in matching human selection, revealing a bias that might not otherwise have been spotted.
In 2016, an intelligent Microsoft-developed
chat-bot called Tay was given a Twitter account. It soon learned from its interaction with the public to post sexist and racist Tweets, “Tay in most cases was only repeating other users’ inflammatory statements, but the nature of AI means that it learns from those interactions.”iv
While machine learning can replicate human bias, AI can help identify it and provide transparency about discrimination. But, proper governance is necessary and would include monitoring outcomes to reveal whether any bias in past human decision-making has been codified. Unfortunately, this may be more difficult in the future, due to complex data architecture across neural networks.
Horizon scanning for risk
The pace of change is making it hard for regulators to anticipate potential risks. New regulation is normally only enacted following a scandal, but several nations have issued AI plans, road maps or strategies without
While their primary concern may be to maintain their nation’s economic competitiveness, there is also a focus on ethical standards and policies.
Meanwhile, major technology businesses such as Google and IBM have developed ethical guidelines for governing the use of AI that they make widely available. Some technology vendors have also launched open-source tools to address ethical issues like bias and transparency. These include Facebook’s Fairness Flow, Google’s What-if tool and IBM’s AI Fairness 360 and OpenScale Environment.
The Institute for Business Ethics suggests four principles to consider how algorithms are used:v
- Reliability – Do we keep to our promises?
- Honestly – Do we deceive and lie to people?
- Transparency – Do we operate in secret and can we explain our decisions?
- Respect – Do we trample over the interest of others to get what we want?
Whilst these guidelines exist, currently, there
isn’t a 'gold standard' of what is considered
“If the data was about past applications for jobs or loans, for example, it’s possible that the machine will replicate or exaggerate any bias learned from past decision-making by humans.”
Exploitation vs empowerment
New technologies generate data. When people visit a website, they may be identified as a potential customer.
Soon, a friendly face might appear, inviting the potential customer to ask questions via voice call or keyboard. That face will most likely belong to a chat-bot.
Tracking every step
Whether or not visitors respond, data about their journey is monitored through the website. High-level telematics can help retailers and manufacturers see which features attract customers and improve marketing communications or product innovation.
At an individual level, people may receive further targeted communication when they visit related websites. And they may be profiled to help ‘customise content and advertisements’.
But it goes much further. Customer data can be linked to public-domain data to improve customer profiling and behavioural predictions.
Google, Amazon and Facebook first developed huge user networks. Then, by allowing outside applications to interact with their networks, they developed platforms that enhance customers’ experience and attract even more traffic to their networks.
Huge user networks and a
treasure-trove of data
With huge user networks allowing outside applications to interact with their networks, there is a risk of data misuse and losing the trust of consumers. Companies have been exposed for how they have collated consumer data without their consent, building profiles to target them with products, services and even to manipulate them. For example, Facebook’s reputation was badly tarnished when Cambridge Analytica exploited their lack of data governance to gain access to customer data.
Ethical considerations arise for two reasons:
- People give away data for no reward, although that data has value
- Information asymmetry occurs: those providing the data might be exploited by those it empowers.
The ‘security principle’
Under the EU’s GDPR, data controllers must have a lawful basis for processing personal data. Individuals’ consent must be given affirmatively (i.e., not unwittingly or passively). Further regulations apply for sensitive data around ethnicity and health.
Individuals’ rights under GDPR are:
- To be informed
- To access their own data
- To have any inaccurate or incomplete
- To have their data erased — including if held by third parties
- To restrict processing
- To transfer their data (data portability)
- To object to their data being processed
- Not to be subject to profiling or automated decision-making
Businesses must comply and respect individuals’ rights, but, the key issue here is the duty imposed on controllers and processors to process data securely. The ‘security principle’ under the GDPR requires that personal data is “processed in a manner that ensures appropriate security of the personal data, including protection against unauthorised or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organisational measures”.vi
Recently, British Airways (BA) was fined a record £183m after people were diverted to a fraudulent site that stole their data. BA had breached the ‘integrity and confidentiality’ principle of the GDPR — also known as the security principle.
More recently, the Federal Trade Commission (FTC) approved a fine of $5 billion against Facebook for “allowing Cambridge Analytica, a British consulting firm to the Trump campaign,
to harvest personal information of its users. The firm used the data to build political profiles about individuals without the consent of
“Data gained about customers can be linked to public-domain data to improve how customers are profiled and their behaviour predicted.”
Ethics and the business benefit
Building trust in business
The Edelman Trust Barometer finds that only 20% of people believe the system works for them. Most sense injustice and want change. Many also worry about job security through a lack of skills, the threat of automation or conflicts about international trade. Yet, 80% trust their employer.
What is the role of business? Should
it help employees to future-proof
Short-termism vs sustainable value
A business exists to generate value. American economist Milton Friedman argued in 1970 that its sole corporate responsibility is to increase its profits. But, as Sir Brian Pitman of Lloyds Bank, explained to CIMA members, Shareholder Value Maximisation is more challenging than a focus on current profits, which can lead to short-termism: “It requires delivering outstanding levels of current performance while building a legacy for the future”x
Michael E. Porter of Harvard has taught us all since the mid-1980s that a business’s value proposition must meet customer needs and it gains competitive advantage through developing its value chain. More recently, he has explained that a business cannot sustain long-term success unless it generates value for its customers, suppliers and employees.
“The purpose of the corporation must be defined as creating shared value, not just profit per se.”xii
“Jamie Dimon and other leaders at some of the world’s largest companies said they plan to abandon the long-held view that shareholders’ interests should come first … “.xiii
The win-win scenario
Over the years, we have seen leading companies focus on technology-related Corporate Social Responsibility (CSR) activities that benefit society whilst boosting their brand and consumer relationship:
- Companies that are embracing digital solutions to pressing social and environmental issues, such as climate change, are finding themselves ahead of the curve. Car companies that invested in electric vehicle technology before it became as widespread as it is now, for example, have the competitive edge in this area over those who did not make the investment earlier.
- With the development of new technology hardware that uses raw materials from our planet and the focus on how organisations use/affect our environment, recycling has started to see a huge uplift. In the last few years, Apple has introduced several initiatives to position its brand as a global technology company that cares and helps the environment. “CEO Tim Cook last month told shareholders the company wants to ‘leave the world better than we found it’”.xiv
- Rather than sourcing as cheaply as possible, businesses that comply with Fairtradexv standards pay their suppliers a fair price. This form of philanthropy can benefit the business through an ethical brand positioning that customers can trust. New digital solutions are appearing in the supply chain transparency space, allowing customers to see the whole journey of the product they are buying from source to shelf. Again, this positions the brand as one that can be trusted.xvi
- In a shared-value approach, suppliers are helping to improve working practices and given security of demand with longer-term contracts. Because their suppliers can rely
on reasonable margins, the business
benefits by having a supply chain built on
- Purpose-led organisations perform better. Blackrock chairman and CEO Larry Fink writes in his 2019 annual letter:xviii “Purpose is not a mere tagline or marketing campaign; it is a company’s fundamental reason for being — what it does every day to create value for its stakeholders.”
Do you take into consideration the wider stakeholders (employees, society and regulators) when strategically investing in new technology for the business?
- Not always/sometimes
Shared value in the digital age
High levels of executive pay, aggressive tax planning and outsourcing of jobs, in addition to corporate scandals, have contributed to distrust in society. When new business models transform industries and automation makes workers’ skills redundant, many people may have cause to feel disadvantaged.
Management accountants must stay alert to external developments and their implications for the business and its stakeholders. For example, McKinsey suggests that businesses risk a backlash from customers, society and regulators unless they consider stakeholders as well as investors when addressing the risks of AI and analytics:xiv
“A business cannot sustain
long-term success unless it generates value for its customers, suppliers and employees and continuously invests in developing its business model.”
a framework for
Ethics goes beyond compliance
Compliance with regulations is not a high enough hurdle to build the confidence of customers and stakeholders. Trust and confidence are only won by meeting expectations. When in doubt about the ethics of an issue, transparency provides a pragmatic test: What might be the impact on trust if the details were made public?
IBM’s principles for Trust and Transparency with regards to AI and data analytics are instructive:xx
EY points out that the risks in AI go beyond mathematics. Systems can malfunction, be corrupted and codify human biases. EY suggests a governance framework emphasising the systems in which AI is embedded:
“To achieve and sustain trust in AI, an enterprise must understand, govern, fine-tune and protect all of the components embedded within and around the AI system. These components include data sources, sensors, firmware, software, hardware, user interfaces, networks as well as human operators and users.”xxi
The role of management accountant
Management accountants have an important role to play in ensuring that business unit managers, colleagues and suppliers are alert to ethical considerations. They can make certain that the business’s values and expectations are fully embedded in all decision-making and performance management.
Some steps you can take today to ensure you’re ready for the new ethical issues of the digital
- Make sure you have the knowledge you need to understand the technology. Clearly, not everyone in a company needs to be able to write or understand the algorithms in an AI solution. However, leaders in a company could be ultimately accountable if there is an ethical lapse within their organisation, so it’s important that you at least understand what data is being fed in, what assumptions are being applied and what decisions are being made based on this information.
- Review your company’s policies, procedures and training on ethics and ensure they are fit for purpose and refer specifically to digital disruptors as they are being used in your organisation. Whilst tone from the top is key, an ethical culture does not come from senior leadership alone — it is the responsibility of every employee, so it is vital the right frameworks are in place to ensure expectations are clear.
- Be curious. If a new technology is brought in, ask the questions of the experts early on to ensure the ethical issues are considered before you commit. The ethical decision in some cases is to say no to bringing in a new form of technology if the company cannot be certain it can handle the possible issues and dilemmas which will arise.
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Explore more resources here.
- i Can AI be ethical? Why enterprises shouldn’t wait for AI regulation, Schatsky D, Kaytal V, Lyengar S,& Chauhan R, Deloitte Insights 2019
- ii Guide to the General Data Protection Regulation
- iii A blot on the profession, British Medical Journal 1988, Lowry S & McPherson G
- iv Tay, Microsoft's AI chatbot, gets a crash course in racism from Twitter
- v Corporate Ethics in a Digital Age, Peter Montagnon, Institute of Business Ethics 2019
- vi The ‘security principle’ under GDPR and personal data breaches
- vii F.T.C. Approves Facebook Fine of About $5 Billion
- viii Edelman Trust Barometer, Annual Global Study 2019
- ix The Social Responsibility of Business is to Increase its Profits, Milton Friedman, The New York Times Magazine, 1970
- x Secrets of the knight revealed (Sir Brian Pitman), Cathy Hayward, Financial Management, CIMA, November 2003
- xi The Big Idea: Creating Shared Value, Porter, Michael E & Kramer Mark R, Harvard Business Review 2011
- xii The Big Idea: Creating Shared Value, Porter, Michael E & Kramer Mark R, Harvard Business Review 2011
- xiii JPMorgan’s Dimon Among CEOs Rejecting Investor-Centric Model
- xiv Apple Will Now Recycle Any Product You Give Back—and Give You Credit for It
- xv https://www.fairtrade.net/
- xvi A Customer Centric Approach To Supply Chain: Supply Chain Journey Mapping (SCJM)
- xvii Shared value supply chains: the business case for mutualism
- xviii https://www.blackrock.com/corporate/investor-relations/larry-fink-ceo-letter
- xiv How do you teach AI the value of trust? EY 2018
- xx https://www.ibm.com/blogs/policy/wp-content/uploads/2018/05/IBM_Principles_OnePage.pdf
- xxi How do you teach AI the value of trust? EY 2018
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Associate Technical Director of Research —
Head of Future of Finance Research
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