How To Be A Responsible AI-Driven Organization

For today’s organizations, artificial intelligence (AI) is more than a promising idea — it is a new imperative. For companies to stay competitive and relevant in their sector, enterprises increasingly need to transform to become AI-driven. Furthermore, AI is a new key to improving business processes, making better decisions, monetizing data, increasing security and much more.

Additionally, the growing importance of AI in the firm is a point that industry observers now emphasize. Ninety-five percent of business leaders foresee that AI will have a substantial impact on jobs. Also, significantly affecting the overall productivity of a company by 2030.

“As AI technologies standardize across industries, becoming an AI-driven organization will likely be table stakes for survival. And that means rethinking the way humans and machines interact within working environments.” — Deloitte

Leaders of forward-looking enterprises are investing in AI-Driven Solutions

“Seven of the ten most valuable public companies in the world are using deep learning and AI at the heart of their operations.” — Michael Dell

Intersetingly, in this new era, organizations are re-imagining every aspect of their:

• operations to create efficiencies
• businesses to grow new capabilities
• products and the ability to design better products
• services to deepen customer relationships

These are all among the many benefits of AI-driven firms. Enterprises are now using AI to perfect logistics and supply chains, to enable predictive maintenance of machinery, to drive higher sales with personalized product recommendations, to streamline customer interactions in call centres, and to create new products and services. The possibilities created by AI systems are endless.

Blockchain and AI — the New Dynamic Duo

Blockchain and AI technologies working together are the new dynamic duo. Blockchain — encrypted, distributed ledgers will unlock new frontiers for AI-driven another innovative technology.

Consider that AI is the theory and practice of developing and building machines capable of performing tasks that require knowledge. Today, cutting-edge technologies striving to make this a reality include machine learning, artificial neural networks, and deep learning.

Meanwhile, the blockchain, at its core, is a new filing system for digital information. Moreover, it stores the data in an encrypted, distributed ledger format and saves copies across many computers. This feature enables the creation of tamper-proof, highly robust datasets which are read and updated only by those with permission.

The academic community has written extensively on the potential of combining AI and blockchain technologies. However, real-world applications are sparse now. This situation will change soon.

Blockchain and AI are two ground-breaking technological trends. However, they will become even more revolutionary — the new dynamic duo — when we design systems that have them working together. Both enhance the capabilities of the other, while also offering opportunities for better oversight and accountability.

We Now Have All the Elements For AI

For entities that recognize the need to become AI-driven, all the essential elements are now in place. These elements include:

• faster networks
• an abundance of affordable computing and storage
• new algorithms
• pre-validated solutions for machine and deep learning
• massive amounts of data

So, when you put it all together, and AI becomes more accessible than ever before, even to small and midsize businesses. As an example, we offer the AI-Auditor to firms of all sizes to enhance audit and internal capabilities. It takes auditors about 30 hours to assemble data to sample three percent of transactions. The AI-Auditor supplies a risk ranking of 100 percent of the transactions in 15 minutes. Auditors have an added 30 hours available to apply professional judgment to strengthen systems.

Increasingly the deluge of data from enterprise systems, the Internet of Things (IoT), social media, and other channels is seen less as an IT problem and more as a business opportunity. Moreover, this is an exciting twist for AI. The massive amounts of data are essential for training machine learning and deep learning applications that are at the heart of AI solutions.  At the end of the day, this function is a top data and analytics trend.

“The very challenge created by digital disruption — too much data — has also created an unprecedented opportunity. The vast amount of data, together with increasingly powerful processing capabilities enabled by the cloud, means it is now possible to train and execute algorithms at the large scale necessary to finally realize the full potential of AI.” — Donald Feinberg, Gartner

Overcoming Barriers in AI-Driven Organization

While it is a giant step forward to have all the components in place, AI initiatives pose weighty challenges for organizations that are becoming AI-driven. Organizations often struggle with issues related to data governance, quality, and availability. Notably, many lack in-house data-science skills and have trouble recruiting data scientists. Moreover, the implementation of AI in the firm frequently requires changing the course of well-established processes.

However, none of these challenges are insurmountable. Fortunately, there is a broad ecosystem working to knock down all the barriers to become AI-driven.

Consider the various technology companies now offer automated machine learning capabilities that help people with little to no data science skills to develop and deploy machine learning solutions. However, this ecosystem is making AI development platforms easier to deploy and use. Nauta, an Intel-initiated data science workbench, is designed to run deep learning models in container environments on systems based on scalable processors.

There also are new off-the-shelf solutions that simplify and speed AI deployments. These solutions streamline the installation of AI applications by delivering machine learning and deep learning platforms. The systems enable data scientists to spend their time building models instead of building infrastructure.

The New Workforce

There are growing concerns in AI-driven organizations that AI will take over the workforce and replace them with AI or other machines. Futhermore, according to various reports, half of the jobs could be automated within the next decade. Although a step forward in technology, some organizations may start to cut down on their workforce to introduce more automated labour. It is expected that in the next few years the everyday human tasks will be transformed, AI technology is no force to be reckoned with now. Today, 80 percent of enterprises all over the world are presently using AI technology currently in their product production.

We are not living in the golden age of AI. However, we are living in the golden age of AI-enhanced productivity. AI is powerful enough to solve many complicated tasks. Moreover, it is not so powerful that AI seems threatening. So, for more thought-intensive, subjective work, we still need humans. That labour shift is unfolding across industries. Welcome to the Era of the AI Coworkers.

The Washington Post has published more than 850 stories, with human reporters and editors adding analysis and interesting details about the transition. For example, in graphic design, the AI tools generate a first pass at designs; however, the final execution remains with the human designers. In film and publishing industries, new AI tools are freeing up editors from the submissions queue.

These AI tools are like young assistants on steroids: They are extremely competent and prolific. However, they still need a seasoned manager to do the heavy intellectual lifting. Moreover, that manager must get on board with working alongside machines to reap the benefits.

Need for Technological Stewardship in AI-Driven Organizations

“Technology challenges us to assert our human values, which means that first of all, we have to figure out what they are.” — Shelley Turkle

AI has an impact. It is being used in all the industries. AI is becoming an increasingly essential element of our daily lives. Thus, it is only a matter of time until it becomes a large part of society. Technological stewardship is a new paradigm. It calls on those who create and influence technology to step into a more significant, responsible leadership role.

Embracing this role involves expansion of:

• how leaders see their contribution
• who takes part in evolving technology
• the perspectives considered in this evolution
• establishing their principles according to the space that they work in

Board Oversight of Technology

AI and blockchain are already opening an array of previously unimagined opportunities for both the use and abuse of technology. Shareholders implicitly rely on the board to ensure that the organization is taking full advantage of the technology, while steadfastly safeguarding against its misuse. All Boards need to create a high-level board committee — a technological stewardship committee.

The specific imperatives that merit sustained committee attention include:

Leadership

The technological stewardship committee assesses and drives the development of AI and blockchain acumen and foresight within the board and the executive team.

Competitive Advantage

The technological stewardship committee initiates and (with top leadership) shapes strategy for accessing and applying AI and blockchain. They look to create a competitive advantage. This insight includes finding the best mechanisms toward that end — i.e., capital investment, M&A, joint ventures, and strategic partnerships.

Risk

The technological stewardship committee anticipates, and proactively safeguards against the significant vulnerabilities that AI and blockchain may create in terms of privacy violations, security breaches, and unintended negative consequences.

A critical risk is AI and blockchain’s tendency to mimic and amplify human bias — for example, automated talent recruiting and screening — which can lead to discrimination litigation as well as inaccurate operating assumptions.

Ethics

The technological stewardship committee actively watches ethical ramifications arising from technology. Moreover, it ensures the board issues proper and prompt policy guidance. Illustrative considerations include implicit bias, how AI and blockchain could negatively affect current members of the workforce, and “interaction transparency.” This term reflects a person’s right to know when one is interacting with a machine.

Corporate Social Responsibility

The technological stewardship committee champions innovative technology initiatives. They look to supercharge organization efforts to improve societal health, education, sustainability, environmental protection, and other organizational social responsibility priorities.

Principles of Technological Stewardship.

Concluding Thoughts

“Policymakers have to be educated about what AI is the issues that might come up and possible concerns. Moreover, for the people who build AI, it’s important to be transparent and clear about what they do.” — Francesca Rossi, IBM

We have reached a point in human evolution where the rate of change of technology has exceeded our ability to adapt — at least in our historically typical manner. It is moving to be regulated rapidly. We need AI-driven organizations to lead in a responsible manner.

With solutions making AI systems easier all the way around, an AI-driven organization can now shift the focus to bigger-picture issues. What entities need most is a vision for using AI throughout the enterprise, an AI strategy endorsed by the Board and C-suite. Moreover, a stepwise action plan for realizing the vision and a technological stewardship committee to enable effective board oversight, so the technology is deployed in a manner that is beneficial for all.