Governance refers to the organizational framework, processes, and policies that underlie institutional accountability, strength, and resilience.
With organizations increasingly digitized, data governance has been rising in importance. Being a responsible steward of private data is central to good governance in the digital age, not only to meet expanding data regulations but also to remain aligned with growing social sentiment around the issue.
Following in the wake of big data, A.I. algorithms are being relied upon for analysis, to make predictions, and to inform critical decisions. Governance of algorithms and the machine learning process is important to understand and mitigate against inherent bias as well as to ensure transparency, accountability, and security. Transparency of deep learning models can be especially challenging with its many hidden layers- why they are often referred to as "black boxes."
Diversity seen in the boards of directors and other leadership roles reflects a diversity of thought and mind to effectively manage in a milieu of diverse communities and environments.
Fraud, Corruption, Waste:
Good governance from frameworks imbued with monitoring, controls, and policies acts to prevent fraud, corruption, and waste from both internal operations and external supply-chains, vendors, and suppliers.
Environmental , Social:
Sound governance interlinks with the management of social and environmental risks and is poised to take advantage of opportunities. A well structured governance framework includes active monitoring, controls, and policies to adapt to fluid social and environmental dynamics.
Regulations, Recommendations, & Reporting:
Laws, regulations, and recommendations from governing bodies are everchanging and have significant impact on operations and the business environment. Adhering to current rules and anticipating policy shifts demands careful attention, active compliance frameworks, and predicative capabilities. Reducing uncertainty of both the past, present, and future, reduces risks, and allows for the proper planning of company roadmaps and strategy.
Reporting is central to good governance and a requirement of many regulations. Reporting fosters accountability and transparency. Reporting of ESG factors is moving from recommendations to regulations in may large jurisdictions of the world.
Deep learning can be leveraged for many governance functions. Anomaly detection to defend against fraud and waste is a mature area of machine learning and used by a growing number of organizations. Optimization of resource allocation can also be part of governance frameworks and can contribute to the resiliency and sustainability of an organization.
Predicting future outcomes to anticipate material change in global and regional governance postures is a promising area that requires taking a holistic look at social, environmental, governance, and private sector factors.
Governance of environmental and social considerations is also given a significant boost with deep learning and other machine learning algorithms. See Social, Environmental.