The Ethics of Big Data and AI

Table of Contents

Introduction to the Ethics of Big Data and AI

Having someone following you and recording your location, body movements, and other little details while you walk down the street is something straight out of a nightmare. Behaviour similar to this is not tolerated in the physical world, then why is it so easily accepted in the virtual realm? 

Every step in the digital world is recorded in this age of artificial intelligence and big data. Big data has taken time to evolve into the state it is today, and even then, the debates regarding big data ethics have yet to conclude. With every company using data collected from users, big data privacy and ethics is a topic that needs much consideration before incorporating even more tech into the world.

Understanding the Ethical Considerations Surrounding the Use of Big Data and AI

To understand the ethical considerations around big data, you need to have a solid way of conceptualizing it. Often, big data is defined with the help of its volume, variety, and velocity.

  • Volume refers to the vastness of the amount of big data.
  • Variety is the different formats you can obtain big data.
  • Velocity describes the incredible speed at which big data is processed.
  • Value is the quality of insights that can be gathered from processed data.
  • Veracity can be used to describe the quality of data being processed. High veracity suggests that the data contains highly insightful information, whereas low veracity means the data is, more or less, noisy. 

Adding to this, understand that almost 2.5 quintillion data bytes are generated daily. Even though big data has given the world useful innovations like AI and IoT, certain information in the wrong hands can prove dangerous. More than half the world does not understand why the government and companies collect data. In contrast, another chunk of the population does not trust others with essential data. In light of this, it is imperative to ask if the defined lines of informed consent, privacy, and ownership are maintained. 

Even in the case of AI, ethical issues surround topics like the impact of machine-human interactions, keeping AI bias away, staving off artificial mistakes, security from adversaries, and so on. Even while utilizing these tools for digital marketing, users are still sceptical about what organizations do with the unlimited data stored in silos.  

The Role of Data Privacy and Security in the Use of Big Data and AI

Data privacy and security take on greater importance in the face of big data and AI. With everyone implementing measures to collect data, having the right defence in place is critical. Even though more data helps AI make accurate decisions, how the information is used can negatively impact many lives. For instance, the recent buzz created by generative AI has people questioning how these systems were trained. If tech giants train their AI bots with art from creators without their permission or compensation, then is AI art ethical? AI ethics and society is an area that needs thorough investigation as the tech grows in popularity.

You can start with security measures such as encryption and access control to protect information privacy and safety. Ensuring authorized bodies use your sensitive information is another way to build your defence system. It is always recommended to devise a plan to help you respond when a data breach occurs. Such a plan can include steps to manage an event of this kind, assess the damage, and include measures to prevent repeat events. The incorporation of machine learning technology in data privacy and security systems has proven effective in analyzing patterns, predicting attacks, and fighting them off early on.

Best Practices for Ensuring the Ethical Use of Big Data and AI

There is a vast difference between defining AI and big data ethics and implementing them. Most of the time, blending ethics and morals with tech can seem outlandish, but this is required to safeguard users’ privacy and security. A few ways in which big data ethical issues can be resolved include:

Actionable Ethics

For ethics to be incorporated into systems at every level, its definition must be specific. All the relevant stakeholders in a company must reflect this commitment to AI ethics. Data protection, consumer-oriented behaviour, and responsible and lawful practices should be involved in the tech that is utilized and delivered. 

Diverse Experts for Input

A cross-functional team of experts to guide the various processes, including design, development, deployment, and so on, can help reduce the bias in big data and AI systems. Such a team can ensure that future and existing uses contain no big data and AI ethical issues. With diverse skills and views, the company will be able to identify potential issues early on in the product lifecycle and rectify the errors before damage is caused.

Leverage Customer Collaboration 

It is advantageous to have a customer advisory council to give their input on the tech designed for users like them. Throughout the development of AI and big data tools, getting feedback from future users can help companies adapt the programs to benefit the right population. At the same time, companies can also address the ethical dilemmas in AI that users have during the earlier days of designing.

The Impact of Unethical Use of Big Data and AI on Individuals and Society

It is no secret that data is not safe these days, despite the claims tech giants make. There have been more than enough instances to show that unethical use of big data and AI, as well as biased use of this tech, can leave lasting impacts on individuals and society. 

For instance, it is public knowledge that smart speakers often listen in on the conversations around them. This helps them pick up essential data that aids marketing campaigns later. Another instance is Instagram’s AI algorithm, which favours pictures of users with more skin. Especially for younger users, having their posts receive less organic engagement because there is not enough skin on display can become dangerous. That is not all; ethical issues in AI involve everything from deep fakes to data tracking that can impact voting behaviour, as seen in the Cambridge Analytica-Facebook scandal.

The Future of Ethical Considerations Surrounding the Use of Big Data and AI

No matter how advanced AI and big data appears, it must be mentioned that they are only emerging technology. There is still a long way to go in this field, and the same goes for the future of AI and big data ethics. Regulatory bodies that address AI and big data ethical issues are also in their nascent stages, so it is quite early to tell if the data that is collected is being used correctly or whether it is safe to trust the processes. Truly, there needs to be an appropriate blend of human morals and machine intelligence to strike the balance that the world needs today.

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