Build an Ethical Platform for AI

AI ethics

A remarkable time of human promise has been ushered in by the convergence of the ever-expanding availability of big data, the soaring speed and stretch of cloud computing platforms, and the advancement of increasingly sophisticated machine learning algorithms.

This brave new digitally interconnected world is delivering rapid gains in the power of AI to businesses. Innovations in AI are already dramatically improving industries such as healthcare, education, manufacturing, legal, transportation, supply chain, energy, and environmental management - virtually all industries and commerce segments. These bounties are, in fact, likely just the start. Because AI and machine learning systems organically improve with the enlargement of access to data and the growth of computing power, they will only become more effective and useful as the hyper-information age continues to develop exponentially grow. It may not be long before AI technologies become gatekeepers for the advancement of corporate governance, public administration, safeguarding vital public interests and sustainable human development.

This prospect that progress in AI will help humanity to confront some of its most urgent challenges is exciting, but legitimate worries still abound. As with any new and rapidly evolving technology, a wide divergence in profit motives and ethics may emerge. It may be due to a steep learning curve that mistakes and miscalculations will be made and that both unanticipated and harmful impacts will inevitably occur. AI is no exception.

In order to manage these impacts responsibly and to direct the development of AI systems toward optimal public benefit, industry and business leaders will have to make considerations of AI ethics and safety as a first priority in the transformation.

This will involve integrating considerations of the social and ethical implications of the design and use of AI systems into every stage of the delivery of your AI projects. It will also involve a collaborative effort between the senior management, financial staff, product managers, data engineers, domain experts, delivery managers and the marketing team in your organization to align the development of artificial intelligence technologies with ethical values and principles that safeguard and promote the values of your organization and wellbeing of the employees and communities that these technologies affect.

We can provide you with guide and the conceptual resources and practical tools that will enable you to steward the responsible design and implementation of AI projects in your organization.

"AI ethics is a set of values, principles, and techniques that employ widely accepted standards of right and wrong to guide moral conduct in the development and use of AI technologies".

These values, principles, and techniques are intended both to motivate morally acceptable practices and to prescribe the basic duties and obligations necessary to produce ethical, fair, and safe AI applications.

An ethical platform for the responsible delivery of an AI project

Building a project delivery environment, which enables the ethical design and deployment of AI systems, requires a multidisciplinary team effort. It demands the active cooperation of all team members both in maintaining a deeply ingrained culture of responsibility and in executing a governance architecture that adopts ethically sound practices at every point in the innovation and implementation lifecycle.

This task of uniting an in-built culture of responsible innovation with a governance architecture that brings the values and principles of ethical, fair, and safe AI to life, will require that you and your team accomplish several goals. As the head of your organization:

• You will have to ensure that your AI project is ethically permissible by considering the impacts it may have on the wellbeing of affected stakeholders and communities.

• You will have to ensure that your AI project is fair and non-discriminatory by accounting for its potential to have discriminatory effects on individuals and social groups, by mitigating biases that may influence your model’s outputs, and by being aware of the issues surrounding fairness that come into play at every phase of the design and implementation pipeline.

• You will have to ensure that your AI project is worthy of public trust by guaranteeing to the extent possible the safety, accuracy, reliability, security, and robustness of its product.

• You will have to ensure that your AI project is justifiable by prioritizing both the transparency of the process by which your model is designed and implemented, and the transparency and interpretability of its decisions and behaviors.

This architecture is called an "Ethical Governance Platform" for two important reasons. First, it is intended to provide you with a solid, processed-based footing of values, principles, and protocols— an ethical platform to stand on—so that you and your team are better able to design and implement AI systems ethically, equitably, and safely.

Secondly, it is intended to help you facilitate a culture of responsible AI innovation—to help you provide an ethical platform to stand for—so that your project team can be united in a collaborative spirit to develop AI technologies for the public good.

Preliminary considerations about the ethical platform

Our role as consultants is to provide you with guidance that is as comprehensive as possible in its presentation of the values, principles, and governance mechanisms necessary to serve the purpose of responsible innovation.

The nature of your organization and the complexity of AI projects will certainly play an important role in designing the conceptual platform. For example a machine learning algorithm trained to detect spam emails presents fewer ethical challenges compared to one trained to detect cancer in blood samples. Similarly, image recognition systems used for sorting and routing mail raise fewer ethical dilemmas compared to the facial recognition technologies used in law enforcement.

Low-stakes

AI applications that are not safety-critical, do not directly impact the lives of people, and do not process potentially sensitive social and demographic data will need less proactive ethical stewardship than high-stakes projects. You and your project team will need to evaluate the scope and possible impacts of your project on affected individuals and communities, and you will have to apply reasonable assessments of the risks posed to individual wellbeing and public welfare in order to formulate proportional governance procedures and protocols.

Be that as it may, you should also keep in mind that all AI projects have social and ethical impacts on stakeholders and communities even if just by diverting or redistributing limited intellectual, material, and economic resources away from other concerns and possibilities for socially beneficial innovation. Ethical considerations and principles-based policy formation should therefore play a salient role in every prospective AI project.

Three building-blocks of a responsible AI project delivery ecosystem

Setting up an ethical platform for responsible AI project delivery involves not only building from the cultural ground up; it involves providing your team with the means to accomplish the goals of establishing the ethical permissibility, fairness, trustworthiness, and justifiability of your project. It will take three building-blocks to make such an ethical platform possible:

1. At the most basic level, it necessitates that you gain a working knowledge of a framework of ethical values that Support, Underwrite, and Motivate a responsible data design and use ecosystem. These will be called SUM Values, and they will be composed of four key notions: Respect, Connect, Care, and Protect. The objectives of these SUM Values are (1) to provide you with an accessible framework to start thinking about the moral scope of the societal and ethical impacts of your project and (2) to establish well-defined criteria to evaluate its ethical permissibility.

2. At a second and more concrete level, an ethical platform for responsible AI project delivery requires a set of actionable principles that facilitate an orientation to the responsible design and use of AI systems. These will be called FAST Track Principles, and they will be composed of four key notions: Fairness, Accountability, Sustainability, and Transparency. The objectives of these FAST Track Principles are to provide you with the moral and practical tools (1) to make sure that your project is bias-mitigating, non-discriminatory, and fair, and (2) to safeguard public trust in your project’s capacity to deliver safe and reliable AI innovation.

3. At a third and most concrete level, an ethical platform for responsible AI project delivery requires a process-based governance framework (PBG Framework) that operationalizes the SUM Values and the FAST Track Principles across the entire AI project delivery workflow. The objective of this PBG Framework is to set up transparent processes of design and implementation that safeguard and enable the justifiability of both your AI project and its product.