Machine learning and artificial intelligence will be the key enablers in a new era of digital experiences and value propositions, but the revolution needs a human touch. Keeping interactions between your AI and your clients fair and unbiased will be critical to the success of your business.

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Even though machine learning and artificial intelligence will be key requirements in your future business, the digital revolution needs a human touch. Why are human values so important to the success of artificial intelligence, and what does this mean for your business? What can you do to eliminate bias in machine learning and ensure that your AI behaves as a good citizen? We will dive into Citizen AI, as illustrated in Accenture’s Technology Vision for 2018.

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The AI revolution needs a human touch

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Artificial intelligence is expanding into every facet of our lives, driving better business decisions and user experiences throughout a wide range of markets and industries. AI has effectively become a new user interface, making our interactions with the increasingly advanced technologies that surround us easier and more seamless. Intelligent digital assistants like Siri live in our smartphones, helping us reach out to others, find information, make notes and navigate the physical world. Meanwhile, Amazon Alexa and Google Home have given us the ability to order goods and services without ever seeing a screen.

These developments are constantly making it easier to use advanced technology effectively. Instead of adapting to our machines, we are teaching our machines to adapt to us. But as we train our artificial intelligence to approve mortgages, identify job candidates and treat patients, we must be mindful of our responsibility to society. In a future where artificial intelligence has the power to facilitate every touchpoint from commerce to public services, we must strive to ensure it remains a force for good. We, therefore, have to raise our AI as with great power comes great responsibility. We call it “Citizen AI”.

The Clear and Present Danger of Bias

In the simplest terms, artificial intelligence is a learning system. It grows and matures through data, acquiring new insights and capabilities based on the inputs we feed into it. In order to guide the training process in the right direction, data scientists carefully tailor those datasets to promote the goals an AI is meant to achieve. But that data can also confer unconscious bias and hidden prejudice.

Last year, researchers at Carnegie Mellon found that Google’s advertising algorithms were six times more likely to display ads for high-income jobs to men than they were to women. In another well-publicized incident, the first version of Google Photos tagged people of color as gorillas. And when ProPublica dug into the workings of COMPAS, a tool used to predict recidivism rates among criminals as part of the parole process, they were shocked to discover it discriminated against minorities.

These are extreme examples, to be sure, but they illuminate a fundamental challenge in artificial intelligence. As we continue to expand our use of these technologies, we must create a strong ethical framework for artificial intelligence and maintain control over the choices it makes.

Unlocking the Black Box

Training AI is a complicated process. Take deep learning, for instance: a pattern recognition method that mimics the way the human brain works and applies those principles to neural networking. This technique has allowed businesses to make substantial progress in highly complex fields such as image recognition. Where humans see a cat, a goat or a tomato, a computer will only see a field of pixels. Deep learning has given computers the ability to recognize what those pixels represent – but we can’t fully explain how the system works, even though we programmed the basics ourselves.

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Where humans see a cat, a goat or a tomato, a computer will only see a field of pixels

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This is a surprisingly common phenomenon. The neural network powering Google Translate invented its own common language to aid in translations, even though it wasn’t specifically instructed to do so. Similarly, the algorithms that help Stitch Fix curate new outfits might accurately capture your preferences without providing clear insights into the reasoning behind the suggestions you receive.

Naturally, this lack of insight into the inner workings of AI is rarely a problem when the results are positive. If efficiency is up and users are happy, why worry? But the case of Microsoft’s Tay chatbot reveals that things aren’t quite so simple. Within just 24 hours of the chatbot’s Twitter debut, it had transformed from a capable conversationalist into an equally capable racist. Although the project was intended as an experiment from the start, it clearly illustrates the potential for disaster when AI is sent out into the world without proper guidance.

It goes without saying that parents are highly motivated to raise their children well and teach them how to be responsible adults. Companies should feel the same duty of care towards their AIs.

Raising Responsible AI


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In order to seize the growth opportunities that artificial intelligence provides, your company will need to address core ethical considerations and establish a set of value-driven requirements to guide the deployment of your AI.

At Accenture, we’ve developed the Responsible AI approach to help our clients create the proper governance frameworks to evaluate, deploy and monitor artificial intelligence. Our methodology focuses on architecture and solutions that emphasize people and human values. Using this approach will help you guide the implementation of artificial intelligence in a positive direction and establish the prerequisites for future growth.

1. Robust Governance

AI must be anchored to your core values as a company. Establishing strong governance with clear ethical guardrails and accountability frameworks will allow your artificial intelligence to flourish.

2. Trustworthy Design

Consumers will only be able to trust your AI as far as you can explain its actions and decisions. Achieving that trust requires privacy, transparency and security to be built into the design by definition.

3. Effective Monitoring

Once your AI is out in the wild, monitoring its performance against value-driven metrics is critical to its success – and yours. You must guard against bias while ensuring accountability and security.

4. Workforce Reskilling

Introducing AI will impact individuals within your organization as well. With Accenture’s myLearning technology, you can democratize artificial intelligence learning and reduce barriers to entry.


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Technology Vision 2018: 5 Leading Trends for Human-Machine Collaboration

Innovative technology-based products and services are changing the way we work and live, while businesses are driving unparalleled societal change. In this year’s Accenture Technology Vision, five emerging trends have been highlighted that will spur this transformation. 

Read more

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A Window on the Future

To say the world is changing quickly would be an understatement. In many cases, what we tend to think of as the future is already here. Functional autopilots in cars and machine-run corporations may not be fully realized yet, but they are already far closer to science fact than science fiction. And it’s not just that technology is accelerating – the rate of acceleration is accelerating as well.

When Google DeepMind created AlphaGo, the first program to beat a professional human Go player, it did so using datasets derived from human experts. The next iteration, AlphaGo Zero, surpassed the abilities of its predecessor within three days and essentially became the world’s best player in forty – all without human intervention or access to historical data. This incredible level of self-improvement and progress in machine learning is an accurate predictor of the road ahead of us.


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Over the next decade, we will surround ourselves with a growing number of autonomous systems. They will be indistinguishable from experts in many ways and we will increasingly wonder whether we are dealing with humans or machines in everyday digital interactions. But no matter the answer, we will expect to be treated fairly either way.

Why Responsibility is Key

In the coming years, organizations such as your own will have an enormous opportunity to weave technology into the fabric of our lives in ways that are responsible, empowering and fair. But your ability to reap the rewards of artificial intelligence will depend on your ability to guide and control it.

This reaches beyond the realm of laws and regulations. If your business implements artificial intelligence whose decisions will have an impact on the lives of your customers, you must be mindful of the values you instill in those autonomous systems. Consumers will expect you to be able to explain how and why your AI makes decisions. You will need to be aware of its values. You will need to establish strong governance, monitor performance and test for hidden bias and undesirable traits. And you will need to be able to correct any issues you discover quickly.

This will not be an easy task. Understanding artificial intelligence will require new skills and insights. But if you succeed, your clients will be even more willing to accept these technologies into their lives. This, in turn, will allow you to get much closer to them and provide better services than your competitors, giving you an invaluable advantage in tomorrow’s hyper-personalized markets.

Do you want to experience what the Technology Vision 2018 trends can mean for your future business? Book an inspiring and meaningful Deep Dive at Accenture’s NanoLab in Heerlen. Please contact Kelly Claessens for more info.

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