DATA ETHICS

What is Data Ethics?

Data ethics is a branch of ethics that evaluates data practices—collecting, generating, analyzing and disseminating data, both structured and unstructured—that have the potential to adversely impact people and society.

It includes addressing and recommending concepts of right and wrong conduct, with transparency in and defensibility of actions and decisions driven by automated/artificial intelligence (AI) in relation to data in general and personal data in particular.

Why Data Ethics?

Ethical behavior is the new theater for commercial competition. Half of consumers are willing to pay a premium to transact with companies they trust. And 57% will stop doing business with a company they believe has broken their trust by using personal data irresponsibly. Businesspeople have always had to consider ethical issues. But in these unforgiving times, getting data ethics wrong has greater consequences than ever before.

Private customer data and the identity of the person associated with that data needs to remain private and confidential. If data has been collected from a person with their knowledge that is ok, but it should never be exposed or given to other businesses that have their personal identity attached to the data in some way.

Customers who give out their data should also have a complete, open, and transparent view of how their data is being used, if it is being sold for other purposes they initially intended, and they should be able to have control in the flow of their private information.

It is also agreed that data should never interfere with human will. This data should never be used to determine who a person is before another person is able to make up their own minds in regard to said person.

Perhaps one of the biggest, most complex, and controversial issues regarding data ethics is how individual’s data may create unfair biased. Sexism and racism are the biggest concerns. This bias can come from actual humans, but it can also come from machine learning and algorithms. They can learn to make unconscious biases based on certain things.

These are just a few of the main focuses and principles that are being focused on most heavily at the moment. Although there is still much more to learn, discuss, and develop when it comes to the basis of and formation of data ethics

Benefits of Data Ethics-:

• Trust. Businesses that apply the key ethics principles of fairness, privacy, transparency and accountability to their AI models and output can retain trust in how they use their data—and thus build greater goodwill and loyalty, which enhances their reputation and brand value.?
• Fair practices. Unintended bias can creep in from anywhere and negatively impact business decisions. Companies that adhere to data ethics principles and standards can demonstrate their fairness in decision-making.?
• Data privacy compliance. Existing data privacy regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) do not directly address ethics, but there is a significant overlap between key privacy requirements, such as lawfulness and accountability, and the principles of AI ethics. Thus, ensuring ethical AI helps ensure data privacy compliance.

Data Ethics and Customer Trust-:

1.Right to be Forgotten-:Customers must be able to let organizations be able to Forget their data when the work or the objective of the data is finished off.

2.Be quick to respond to Failures-: In spite of world-class technology infrastructure, history shows that organizations can’t promise customers that nothing bad will happen to their digital information. Winning organizations need to recognize, understand and proactively manage potential issues. For instance, after a recent cyber-attack, a communications provider was quick to notify customers and banks of the incident, which helped maintain consumer trust and confidence.

3.Give a Customer delete Button-:Customer must be able to delete their content from the Cyberspace when the job is over.Customer must have 100% control over their data to maintain Data Sovereignty.

Data Ethics Guidance for Organizational Leaders

Startups

For startups developing technology and tools which include AI applications, mindfulness about ethical implications is essential. It can be challenging for small companies to dedicate additional resources to ethical analysis, but it’s even more important that these companies develop these practices early on.?

Small/Medium-Sized Businesses

As many small businesses scale, they may begin to use more technology. Gathering user data, developing purchasing databases, and potentially hiring engineers may all become the norm. However, with these developments comes an exponential growth in related risk.

Leaders in this type of business can prioritize transparency and accessibility as they grow. Keeping customers informed about what data they’ve gathered and how it will be used is key as you continue to develop your processes. Requesting consent and maintaining high levels of communication regarding changes in technology and expectations is another way SMEs can ensure they are growing sustainably.?

Global Corporations

Due to the scale of impact for most multinational corporations, developing reliable security, privacy, and ethics processes are even more critical. Corporations in vastly different industries have fallen victim to ransomware, leaks, and improper use of data by employees; however, claiming ignorance of the risks is no longer acceptable.?

Developing internal, cross-departmental working groups is a valuable first step in developing a company-wide shift in values and knowledge-sharing. Expanding required training for employees and incentivizing regular analysis for managers and individual contributors will also communicate the value of ethical considerations related to data for all.

Data Ethics Regulations

Many people are aware of the importance of data ethics—but what does it mean to us as consumers? What does it mean for companies? What does it mean for government agencies??

The answer to these questions depends on where you live. In some countries, there are already laws in place requiring companies to be transparent about how they handle personal information; in others, there aren't any regulations at all.

And then there are the ethical questions we face every day: How much do we share with each other online? Should we be sharing less? And what happens when something goes wrong? These are all pressing issues that require thoughtful consideration and strong leadership from both government and industry leaders so that our future isn't threatened by unethical behavior or lack thereof.

Around the world, governments are trying new methods of regulating ethical data collection, AI, and various uses for data (ex: targeted marketing, etc.).?

Here are a few regulations worth knowing and following to understand the current state of data regulation where you live:?

Data Protection?

• GDPR (European Union)?
• CCPR, CCPA (USA - California)?

AI Use?

• EU AI Act
• New York Bias in Hiring AI Regulation (USA - NY)?
• Algorithm Justice and Online Platform Transparency Act (USA)

Platform Regulation

• Digital Services Act (European Union)

While the EU and US lead the way in ratified legislation, most of these policies are new and continuously under development.

Way Forward

For those interested in preparing their career for these developing changes in technology and business, there are many which can either facilitate a change or enter into a career in ethical data. Start with our Introduction to Data course, which looks at data ethics and data privacy. From there, you'll find several certifications to explore:?

• Data Privacy
• IAPP Certified Information Privacy Manager (CIPM) certification
• Security PrivacyOps certification
• ISACA Certified Data Privacy Solutions Engineer (CDPSE) certification?
• IAPP Certified Information Privacy Professional (CIPP) certification
• Data Security
• CompTIA Security+
• Certified Ethical Hacker (CEH)
• GIAC Security Essentials Certification (GSEC)
• Offensive Security Certified Professional (OSCP).