Why Data Ethics is a Must for Companies today?

Why Data Ethics is a Must for Companies today?

Data Ethics: What are they? Why do we need it?

The recent Cambridge Analytica scandal highlighted how data abuse can be terrifying and threaten our privacy. Today, we live in a connected world, where data is power. Many companies, websites, apps collect data that are inherently personal and sensitive in nature. This is why we need data ethics and regulations now more than ever. Data ethics is an emerging branch of ethics that looks at and evaluates all of the moral issues that are associated with data. According to Forbes, data privacy legislation like GDPR and CCPA have clear laws and regulations that must be followed by companies strictly. However, data ethics is more nuanced and complicated as it is up to each company to decide what use cases their collected data should support or not.

Why do we need it?

Today, disruptive technologies like AI and machine learning have helped companies by creating fantastic opportunities to deliver better services. Companies need public and user data to innovate, create more efficient and effective products and services, and fuel revenue and productivity. With increased awareness about data misuse, people have become quite cynical about the intentions of many of the companies that rely on our data and information for personalized services. These fears became more prominent in the wake of the Cambridge Analytica-Facebook data scandal that sent shockwaves throughout the world, putting the issue of data privacy front and center. The scandal involved the misuse of millions of people's personal data to allegedly profile voters in the US. Moreover, earlier data security was limited to protection and prevention from cyber threats. Today, enterprises are beginning to understand the vulnerability risks due to a lack of data ethics practices.

Data ethics plays an important role by helping define good practices around how data is collected, shared, and used by organizations. It extends the limits of information ethics by shifting to data-focused instead of being information focused. Data ethics helps in ensuring that the decisions made by analyzing people's data, facilitate generating fair and good outcomes for both the individual and wider society. Therefore, data ethics can be a powerful risk reliever and value creator.

Role of Governing Authorities

Though big data analytics is still in a juvenile phase, enterprises can quickly process large amounts of data and make correlations and predictions using disparate data sets to derive meaningful insights. The ease of these efforts creates numerous issues related to privacy, confidentiality, transparency, and identity. Hence, government bodies must ensure that data controllers engage with the public and develop policies about transparency and accountability in data processing. Additionally, they must take into account, the impact of information-based applications on the rights of data subjects. This is exactly what European Data Protection Supervisor is trying to achieve by encouraging data controllers to design, implement and monitor their data processing activities in an ethics-responsive manner.

What can be done?

While data ethics still may not have well-defined or shared descriptions, there are few aspects that can help safeguard ethical use of data. These include

  • Accountability for making sure data use is fit for purpose and the downstream uses of datasets.
  • Private customer data and identitification should remain private and regularly audited.
  • Customers accessibility to transparent view about how their data is being used or sold.
  • Data sources to be as diverse as possible to prevent institutionalization of unfair biases in training machine learning and AI models.
  • Matching privacy and security safeguards with privacy and security expectations.
  • Maximizing transparency at data source points by explaining methods leveraged for analysis and marketing to data disclosers.
  • Define guidelines for ethical usage of data clearly.
  • Design practices that integrate transparency, configurability, accountability, and auditability.
  • Assign a dedicated and diverse ethics committee that will address and discuss cases that require extra attention. They must combine representative views of both internal and external stakeholders.
  • Conduct risk management and risk benefit assessments.
  • Avoid using data in ways it was not originally intended.

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