HomeAutomationEthical Considerations in Intelligent Automation
Image Courtesy: Pexels

Ethical Considerations in Intelligent Automation

-

As intelligent automation (IA) finds greater absorption across businesses, the ethical issues surrounding it assume critical dimensions. Combining AI with machine learning and automation, IA promises to revolutionize business operations by upping productivity and further enriching customer experiences. At the same time, this transformational technology also raises significant ethical questions that must be carefully examined to ensure its responsible implementation.

ALSO READ: The Rise of Automation-Specific Threats

Privacy and Data Security

Among the top ethical considerations in intelligent automation, privacy ranks high. The generally applicable fact that IA systems require a great deal of data to perform effectively may affect an individual’s right to privacy. Organizations shall handle the collection, storage, and processing of such data with complete transparency about their intent and adherence to relevant regulations regarding privacy, such as GDPR. The sensitive data has to be made safe from leakage and unauthorized access to retain the trust and protect the rights of individuals.

Bias and Fairness

The intelligent automation systems are only as unbiased as the data they are trained on. The IA system projects and further aggravates the biased underlying data. Examples include recruiting processes, whereby an IA system may eventually be prejudicially set against a particular demographic group based on biased training data. Organizations must, therefore, make active efforts toward the eradication of bias in data and the design of IA systems with the view of fairness and equity in mind if this risk is to be mitigated.

Job Displacement and Economic Impact

Automation of tasks previously performed by humans does raise concerns about job displacement and broader economic impacts. While intelligent automation enables higher efficiency and cost savings, there is also a risk of displacing workers, especially in jobs that are repetitive. The social implications of IA have to be considered, and organizations need to develop strategies that take care of workers affected by automation through re-skilling programs, and initiatives on creating new job opportunities, among others.

Transparency and Accountability

As IA systems become increasingly complex, there will be a greater need for transparency regarding decisions made. The stakeholders involved are employees, customers, and regulators who have to understand not only how the IA systems work but also why they decide on one particular solution and not another.

Besides this, the necessary provisions should also be made by organizations regarding accountability mechanisms to handle adverse consequences from the use of IA. That means clearly defining who is responsible for decisions made by the automatic system and that mechanisms are in place to deal with errors or unintended outcomes which may result.

To Conclude

While the prospects presented by intelligent automation are bright, ethical issues of some sort cannot be completely ignored. It will be possible for organizations to responsibly use intelligent automation by paying proper attention to privacy, eradicating bias, tackling job displacement, and ascertaining transparency and accountability. As IA continues to evolve, responsible progress will come from a core ethos of ethics that makes sure technology serves humanity for the greater good.

Samita Nayak
Samita Nayak
Samita Nayak is a content writer working at Anteriad. She writes about business, technology, HR, marketing, cryptocurrency, and sales. When not writing, she can usually be found reading a book, watching movies, or spending far too much time with her Golden Retriever.
Image Courtesy: Pexels

Must Read

Unsupervised Learning in Real-World Applications: What’s Next?

Unsupervised learning is revolutionizing the way we analyze and interpret data. Unlike traditional methods, it doesn’t rely on labeled datasets. Instead, it identifies hidden...