the-next-stage-of-human-machine-collaboration

The next stage of human-machine collaboration

Some AI-based services and tasks today are relatively trivial – such as a song recommendation on a streaming music platform.

However, AI is playing an expanding role in other areas with far greater human impact. Imagine you’re a doctor using AI-enabled sensors to examine a patient, and the system comes up with a diagnosis demanding urgent invasive treatment.

In situations such as this, an AI-driven decision on its own is not enough. We also need to know the reasons and rationale behind it. In other words, the AI has to “explain” itself, by opening up its reasoning to human scrutiny.

The transition to Explainable AI is already underway, and within three years, we expect it to dominate the AI landscape for businesses.

Explainable AI systems will play this pivotal role through their ability to:

Explainable AI, ready for takeoff

The transition to Explainable AI is already underway, and within three years, we expect it to dominate the AI landscape for businesses. It will empower humans to take corrective actions, if needed, based on the explanations machines give them. But how will it do this?

There are three ways of manifesting and conveying the reasoning behind AI decisions made by machines:

  1. Using data from the machine learning – using comparisons with other examples to justify the decisions

2. Using the model itself – explanations mimic the learning model by abstracting it through rules or combining it with semantics

3. Hybrid approach combining both data and model – offers metadata and feature-level explanations.”The future of AI lies in enabling people to collaborate with machines to solve complex problems. Like any efficient collaboration, this requires good communication, trust and understanding.” 

– FREDDY LECUE, Explainable AI Research Lead, Accenture Labs

Two use cases for Explainable AI

No. 1 – Detecting abnormal travel expenses
Most existing systems for reporting travel expenses apply pre-defined views, such as time period, service or employee group. While these systems aim to detect abnormal expenses systematically, they usually fail to explain why the claims singled out are judged to be abnormal.

To address this lack of visibility into the context of abnormal travel expense claims, Accenture Labs designed and built a travel expenses system incorporating Explainable AI. By combining knowledge graph and machine learning technologies, the system delivers insight to explain any abnormal claims in real-time.

No. 2 – Project risk management
Most large companies manage hundreds, if not thousands, of projects every year across multiple vendors, clients and partners. A company’s expectations are often out of line with the original estimates because of the complexity and risks inherent in the critical contracts.

This means decision-makers need systems that not only predict the risk tier of each contract or project, but also give them an actionable explanation of these predictions. To address the challenges, Accenture Labs applied Explainable AI and developed a five-stage process to explain the risk tier of projects and contracts.

Measuring effectiveness

Eight measures can be applied to assess its value and effectiveness. These measures capture the elements that people need in an explanation, but cannot necessarily all be achieved. While explainable AI will use and expose techniques that address these questions, we—as humans—should still expect a trade-off between value and effectiveness.

Comprehensibility

How much effort is needed for a human to interpret it?

Succinctness

How concise is it?

Actionability

How actionable is the explanation? What can we do with it?

Reusability

Could it be interpreted/reused by another AI system?

Accuracy

How accurate is the explanation?

Completeness

Does the “explanation” explain the decision completely, or only partially?

A technology revolution with people at its heart

Explanation is fundamental to human reasoning, guiding our actions, influencing our interactions with others and driving efforts to expand our knowledge. AI promises to help us identify dangerous industrial sites, warn us of impending machine failures, recommend medical treatments, and take countless other decisions.

The promise of these systems won’t be realized unless we understand, trust and act on the recommendations they make. To make this possible, high-quality explanations are essential.

Source: Accenture Lab AI report 2018

Accenture Labs, in a new report, details how we can meet the need for more information by giving AI applications the ability to explain to humans not just what decisions they made, but also why they made them.

Europeans Extend Their Lead in the Industrial Internet of Things

Looking ahead at the investment plans of industrial customers, Europeans are poised to hold a narrowing lead, with more than twice as many extensive implementations in 2020 as their US counterparts. Looking almost 10 years ahead—an imprecise endeavor, but one that can shed light on aspirations—the investment plans of executives in both regions could result in a more competitive position, with the US expecting to see similar levels of POCs and implementations as the Europeans.

The key challenge for both regions remains addressing cybersecurity concerns, not only by the vendors but also for customers, who will need to ramp up their security investments significantly to benefit fully from IoT technologies. Bain research finds that customers would buy more IoT devices, and pay more for them (about 22% more on average), if their security concerns were addressed. Becoming a leader in security remains a powerful opportunity for European IoT champions.

IoT providers in both regions could also speed their progress in reducing barriers by focusing their investments on fewer industries, which would allow them to develop greater expertise and deliver more comprehensive end-to-end solutions to their customers. The learning curve effects from POCs will allow vendors to overcome the implementation concerns of their customers by offering more packaged solutions that can scale more easily.

Partnerships with industrial vendors are especially important, as they provide specific domain knowledge and system integration capabilities. Without these partnerships, IoT vendors may continue to struggle to sell solutions that integrate smoothly with customers’ businesses and processes.

Leading industrial companies are moving quickly past the proof stage, and now, it’s all about scaling. Over the next two to three years, clear winners will emerge, as the benefits of early investment kick in and their POCs scale up to operational levels. Companies that have put off investment will lose ground to competitors that are learning how to derive value from the Internet of Things and becoming more data-driven every day—skills that will form the basis of competition in a world of extreme automation and artificial intelligence.

Bain & Company Official Report Link

Blockchain and Insurance Industry

While the banking sector’s quest for modernization was a major early driver behind the growth in enterprise blockchain technology, the insurance industry has not traditionally had such a healthy appetite for change. That is, until now.

Over the past couple of years, insurers have migrated away from their conservative image, leveraging several emerging technologies, including blockchain, to re-think their current business models.  One of the most significant technologies leading this digital transformation is blockchain which is streamlining back-office processes and systems. Heading into 2019, insurers are accelerating their deployment of the most innovative use-cases of enterprise blockchain technology yet.

Laying the back-office building blocks

Insurance companies face a complex web of challenges in today’s market. Regulatory demands are increasing; fraudulent claims are commonplace and the flow of data is ever increasing. Meanwhile, as digital technology permeates the financial services industry more broadly, customers expect a greater level of innovation than ever before.

Despite the growing demand for tailored products and services, insurers recognized that for transformation to be sustainable, it must begin in the back office. Legacy systems combined with patchwork solutions have perpetuated a closed-off insurance information environment with data silos and resulting operational inefficiencies. Building customer-facing digital solutions on these crumbling foundations would have disastrous consequences.

That is why, over the past two years, insurers have been hard at work behind the scenes deploying cutting-edge enterprise blockchain platforms to overhaul and modernize their back offices. Integrating even just the foundational technology can have a huge impact on a company’s transparency, stability and efficiency.

By taking the first step of moving its transactions onto a shared ledger, an insurer can potentially eliminate fraudulent and duplicate claims by logging each transaction in a decentralized repository. Instantly, an insurance company is able to verify the authenticity of a customer, policy or claim. This is a simple premise but a huge step forward for the industry.

In addition, with the rise of the Internet of Things (IoT) and connected devices, blockchain provides an efficient and secure way to manage, share and leverage an ever-growing amount of data. Purpose-built enterprise blockchain platforms like Corda overcome the challenges of traditional public blockchains by ensuring sensitive data is only shared with parties that have a need to see it in each instance.

The potential efficiency gains for both the insurer and the insured are dramatic. Consider, for example, a re-insurer, insurer and broker consolidating their policy data and storing it on a blockchain – the underwriting and application process could be reduced from weeks or even months to near real-time, with no burden on each entity having to gather, reconcile and submit documents.

These core benefits of blockchain technology are now being realized across the global insurance industry, with forward-thinking initiatives such as the RiskBlock Alliance and B3i leveraging the power of collaboration to drive adoption and deployment.

By moving to a model in which disparate parties such as insurers, reinsurers and brokers can share and store policy information in a cryptographically secure way, the industry has laid the foundations for the next phase of blockchain-enabled innovation.

A convergence of technologies

Insurers are acutely aware of the need to evolve in order to stay competitive, and streamlining market operations with blockchain technology is freeing up precious capital and resources previously spent on auditing and administrative costs.

Newly created roles such as Chief Digital Officer and Chief Innovation Officer are now commonplace across the industry, with firms vying to increase their market share by developing solutions that meet customers’ demands for innovation while increasing efficiency and profitability. Once data has been migrated to a blockchain platform, the potential to apply other technologies such as artificial intelligence (AI) to utilize this immutable, real-time information is vast.

Dynamic pricing is an example of an emerging blockchain-enabled innovation that benefits both the insurer and the customer, with broad-ranging potential across health insurance, car insurance, property insurance and beyond.

Taking the case of shipping insurance, advances in technologies such as AI and telematics enable insurers to access detailed, real-time information about a ship’s location, age and condition. This means, if a ship enters pirate waters, its location data would automatically be updated on the blockchain and the insurer can make the necessary adjustments to its risk profile and policy pricing. The same applies in the converse scenario – for example if a ship is young, in good condition and doesn’t stray from safe waters.

Now consider that the ship is transporting refrigerated cargo, which is also insured. How does an insurer know whether a temperature spike is taking place in a crate at sea a thousand miles from its destination that could potentially destroy the cargo? Thanks to telematics, sensors in the cargo containers can communicate accurate information about temperature, humidity and atmosphere.

This information can be updated in a smart contract on a blockchain platform in real-time, enabling an automatic pay-out to the customer if the cargo is spoiled by high or low temperatures. This saves the insurance company time and money while providing the customer with a better experience.

Dynamic pricing also has huge potential in the health insurance space. Health insurers require a vast amount of information about a customer’s medical history and lifestyle in order to piece together a policy, and provision of false or inaccurate information is commonplace. Blockchain enables insurers to accumulate data from multiple verified sources with updates occurring in real-time, allowing them to carry out more frequent risk assessments and customize pricing accordingly.

Usage-based insurance (UBI) is another innovation currently reshaping the car insurance industry. Many cars now come equipped with connected features or advanced driver-assisted systems (ADAS), which is having a profound impact on the way auto insurers handle policies.

Traditionally, car insurance policies have been based on driver characteristics like age, personal information and accident history. With UBI, insurers are able to incorporate driving behavior data such as speed and hard braking that is updated in real-time on the blockchain. In addition, telematics technology in the car can measure the time a driver spends on the road each day, opening up opportunities for pay-as-you-drive insurance policies that incorporate this data into a smart contract.

A digital future

These developments would be innovative in any sector, but when you consider the processes underpinning the insurance industry have remained largely unchanged for hundreds of years, the evolution is even more dramatic.

By harnessing the attributes of blockchain to tackle back-office challenges head-on, insurers have made the necessary investment to position themselves to take advantage of the myriad of opportunities and further efficiencies that blockchain – and its convergence with other new technologies – will deliver over the coming years.

2019 will undoubtedly see the insurance industry enter the next stage of its digital transformation, and we are proud to play an ongoing role in fostering this innovation with the launch of the first R3 Corda InsureTech Challenge.

Original Article by By: Ryan Rugg, Global Head Of Insurance, R3