According to Mckinsey & Company - "Every company must establish its own best practices for managing its data". Organizations across the world must understand data management ethics to survive the fast-growing technology and disruptions that happen today. Data ethics is by definition guided principle adopted from data regulatory bodies or a designed rule by an organization to protect the privacy of data collected and analyzed.
AI biased is rampant in today's world because data scientists pay so much attention to model accuracy by doing tradeoffs (an ML term used when data scientist tradeoff bias in order to reduce model over-fitting or under-fitting). With that in mind, most businesses have begun to address the operational aspects of data management—for instance, determining how to build and maintain a data lake or how to integrate data scientists and other technology experts into existing teams. Fewer companies have systematically considered and started to address the ethical aspects of data management, which could have broad ramifications and responsibilities.
Business around the world in the recent time begin to build capacity around data and related technologies. Many of these organization hire data scientist, data anlyst and other data experts to compete with the innovating technologies of massive advanced computers which further intensify data processing capacity, however, little or no attention is paid to soruces of data and the need to protect data integrity.
In a 2021 McKinsey Global Survey on the state of AI, for instance, only 27 percent of some 1,000 respondents said that their data professionals actively check for skewed or biased data during data ingestion. Only 17 percent said that their companies have a dedicated data governance committee that includes risk and legal professionals. In that same survey, only 30 percent of respondents said their companies recognized equity and fairness as relevant AI risks. AI-related data risks are only a subset of broader data ethics concerns, of course, but these numbers are striking.
In reference to the above context, one of the major reason companies breaching data regulation policy is short-term ROI illusion - companies around the world are most time swamped in chasing short-term ROI while ignoring data protection and integrity. Chief Operating Officers in these companies would protect his job than protecting data privacy - he needs to provide for his immediate family and he has a target to meet as the team lead saddled with responsibility to generate revenue in the company.
Breaching data policy is not a mere issue as assumed by many organizations who go consumed by the above challenges. Board Members in an organization could bear some legal consequences if this happens.
Data Governance has since realized its value with regulatory bodies established around the globe - The European Union’s General Data Protection Regulation (GDPR) went into effect only in May 2018, the California Consumer Privacy Act has been in effect only since January 2020, and federal privacy law is only now pending in the US Congress. Years before these and other statutes and regulations were put in place, leaders had to set the terms for their organizations’ use of data—just as they currently make decisions about matters that will be regulated in years to come.
WHAT LEADERS AND BUSINESSES NEED TO DO
Overall, Data ethics and management isn't ust for CEOs to drive, it needs to be entrenched in every companies handbook. Every company has to think globally in order to build trust with customers data.
Ultimately without gainsaying, data policies and guiding principles can never be an overnight assignment for businesses to implement. it requires commitment, building a data team, creating relevant policies, and establishing an operational process that protects customers' data and privacy. Unfortunately, companies that disregard this would risk losing customers' trust and value destruction
Author: Rasheed Abulkareem(CBO D-Aggregate)
Reference: Mckinsey & Company
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