by Jeff Felice
The collection, analysis, and aggregation of data for use in advanced analytics has been one of the biggest technological leaps we’ve taken in recent years. As with other major steps forward, it created a new set of challenges. Considering the impact that artificial intelligence and data science has on how we receive and absorb information, and how much data is collected and available for commercial use, it’s imperative to advocate for good data ethics.
Defining and practicing ethical use of data use is simply the right thing to do, yet some companies purposefully obscure the truth, push the boundaries of acceptable use, or freely take advantage of available data. As we’ve seen with other emerging fields in science and tech, legislators are slow to adopt new laws that define ethical practices and protect consumers.
Companies of all sizes must operate with transparency when collecting and harnessing customer data. Most importantly, they must do no harm in their use of data—that includes reducing the harm data has on individuals and groups. Data collection and use will only continue to grow, which means its potential to pose a risk to individuals will increase. As the legal landscape around data ethics takes shape, organizations shouldn’t wait to make data ethics a priority.
While some companies in the field bend the rules or take advantage of legal loopholes, these actions can have serious consequences for consumers, and as we’re beginning to see, companies can also face serious backlash. As more industries become data-focused, data ethics will become even more of a focus point in the business world.
How can data ethics be applied?
You may be working on a data project that needs an extension to train your AI to learn and produce ethical outcomes. Stakeholders and leaders may push to meet the deadlines and skip the ethical technology learning curve.
They may not understand that an investment in ethical data practices will save the company time and money in the future. Allowing AI tools to learn without ethical data practices could open the business to risk and liability.
A data ethics credential or certification can empower you with the knowledge and application of best practices of ethical data use in today’s technological landscape. With this in mind, we’ve outlined some of the benefits of ethical data practices to consider as you navigate the frontier of emerging data technology.
Table of Contents
- Create a Legacy
- Build Trust
- Inspire Others
Create a Legacy
Early adopters of high ethical standards for data science will ensure a positive legacy for their companies. As time moves on and people reflect on the actions of companies, they’ll remember those that acted ethically, as well as those that didn’t. Public opinion can have a huge impact on company valuation and future viability.
Salesforce has developed a reputation for proper data science ethics during buildout of AI (Artificial Intelligence) across its platforms. It added an Architect of Ethical AI to its leadership team and created an Ethical AI Practice group to advise internal proceedings and work with external companies to develop their own standards.
Because of this, Salesforce is now known as a company on the forefront of ethical data use and has received regular recognition for it. In 2022, Ethisphere named Salesforce one of the world’s most ethical companies for the twelfth time.
Since Salesforce is considered an innovator for high ethical standards, this legacy will follow them into the future, ensuring continued success. They’re able to set the standard for ethical data use and direct the conversation, giving them the advantage of trust over the competition.
Trust is all-important in data science ethics. Customers of all types, as well as stakeholders, have to trust that your business is making smart choices that benefit the company and its supporters. Without trust, your business—any business—is dead in the water.
When building a foundation for trust, start with transparency. Too often, companies obscure how they use data throughout the data value chain. While the company may be motivated in the moment to operate in the shadows for short term gain, in the long run, this sort of morally ambiguous behavior undermines the company’s future.
Once your company establishes trust, consumers will know their information is recorded and used safely. With a solid reputation in place, more customers and investors are willing to take a chance on your company, and existing customers will feel good about using the product or service.
Clear and forthright communication is also essential for trust building. Making sure everyone has ample opportunities to learn about data collection and how it’s used is a great place to start. Too few people fully grasp what happens when they provide their data to a company or service.
An often-used example is Facebook. A person signs up for Facebook thinking they will connect with people for free, when in reality the company is collecting their information to sell to advertisers. While many people know that information on how Facebook uses their personal data is available, it’s not explicitly stated. This opaque use of user’s data, along with other factors, has interrupted the growth of Facebook by creating distrust in current and potential users.
More often than not, data ethics mirror business ethics, and the right thing to do is to simply be honest. Standards like GDPR already require companies to tell customers up front what data is collected and sold, and to what purpose. Companies can cultivate trust with the public and improve their reputation by taking it a step further — by providing access to your AI and data ethics principles, as well as being transparent about how data will influence the decisions made by machines and accountable for its use.
If one company practices ethical data principles and succeeds, it inspires their peers to practice good data ethics in their own businesses. Inspiring change creates leaders within the field that other companies can look up to and model their own behavior after.
Tech giant Apple has woven strong data ethics into its company, which is one of the many reasons so many new startup founders use Apple’s ethical data practices as a model for their own. For example, Apple introduced new features to enhance transparency between iOS users and application developers—specifically, a new App Tracking Transparency feature that requires every app to explicitly request user permission to track and share information with third parties. This new requirement demands explicit consent for third-party tracking, which many Apple users were previously unaware of.
Since many new tech companies use Apple as inspiration as they develop their processes, Apple’s dedication to data ethics means these new companies employ similar tactics. Apple’s strong data ethics also inspire the top talent of the world to want to work with them. They can attract the brightest minds because of their progressive thinking.
The conversation around data ethics will only increase as more data is available and companies begin to realize the value of that information. Being at the forefront of this conversation will help you stay informed and make good decisions where your data is concerned.
At CertNexus, our courses in data ethics, data science, cybersecurity, and other emerging technologies were built with input from leading figures in the industry to impart and validate a set of job-ready skills.
If you’re considering a course in data ethics, learn more about how our certifications and credentials can differentiate you in your role and in the job market.
CertNexus is a vendor-neutral certification body, providing emerging technology certifications and micro-credentials for Business, Data, Development, IT, and Security professionals. CertNexus’ mission is to assist in closing the emerging tech global skills gap while providing individuals with a path towards establishing rewarding careers in Cybersecurity, Data Science, Data Ethics, Internet of Things, and Artificial Intelligence (AI)/Machine Learning.
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