With more than 5.3 billion humans using the internet and about 3.5 billion searches a day only on Google, the amount of data generated each day can be thought of as ‘enormous.’ The permission to access this data is given by the users without even reading the data receiving parties.
The lack of a specific purpose or method for the type of usage, storage, and processing often leads to issues faced by multiple business giants of the world. It leads to the requirement for thoughtful consideration to merge Big Data and ethics. Do you feel the same? Multiple authorities agree with your ideology, too. So, there have been certain best practices and ethical considerations on the topic.
Here’s what we’ll cover in the article:
- What is Big Data?
- What Are Big Data Ethics?
- What Are the Ethical Considerations in Big Data?
- What Are the Best Practices to Balance Innovation and Privacy with Big Data?
- What Are the Benefits of Maintaining Big Data Ethics?
- Learning Big Data Ethics with Interview Kickstart
- FAQs About Big Data Ethics
What is Big Data?
Big Data, as evidenced by the name, refers to vast and complex sets of information. It is an integral part of the digital world and derives the business’s growth by modifying the decisions. The constituents of Big Data are wide and include high velocity and variety, massive volumes of structured and unstructured data types. Speaking in general terms. It includes videos, texts, images, and sensor data. It is processed by techniques like generic algorithms, Machine Learning, classification tree analysis, regression and sentiment analysis, and much more.
Alt-text: 3 V’s of Big Data
What Are Big Data Ethics?
The branch of ethics that focuses on responsible and moral-based usage of Big Data is Big Data ethics and is currently the need of the hour. The ease of access due to increasing cyber crimes, misuse of data, and increased personal data usage without consent has posed challenges to many organizations. Ethical regulations are crucial in all aspects of Big Data handling, which includes collection, storage, and analysis.
What Are the Ethical Considerations in Big Data?
The ethical considerations to combat Big Data ethical concerns require a focus on the following aspects of data handling:
- Privacy: The need particularly arises while handling sensitive data that includes personal information. Irresponsible usage or sharing violates individuals’ right to privacy.
- Security and data breaches: It is an unavoidable situation that can occur at any time. Leakage of data or improper handling on contact with hackers or thieves leads to issues and violations of people's rights.
- Accountability: Lack of an accountable team or person on the occurrence of crimes or improper handling of individuals’ private data leads to further chaos. It leads to a lack of individuals or teams to rectify, undo, or minimize the problems caused by the actions.
- Consent: Informed consent on what is being used along with who will be using the data helps individuals take mindful steps on internet usage.
- Environmental impact: The Big Data usage includes the energy consumption. Its environmental impact on usage, storage, and processing, along with the manufacturing of hardware and other components, is an important consideration in ethics.
- Data ownership: The doubts on ownership and governance of data remain valid, leaving the question of responsibility for ethical considerations.
- Fairness: Discrimination and bias is common in Big Data. Improper processing or usage will produce biased and unfair results.
What Are the Best Practices for Balancing Innovation and Privacy with Big Data?
Businesses find it challenging to escape from ethical issues of Big Data and associated problems. Responsible usage is under their control and must be practiced to avoid associated harmful consequences. Here are some best practices suggested to balance innovation and privacy with Big Data:
Regulated Data Collection
Obtaining the data that is actually required rather than bulk collection is an actionable task. All it requires is thoughtful planning to identify the purpose and data. Excessive information leads to negative costs for the company by neglecting the storage of data, making it prone to theft. Further, privacy violations and data misuse are also common.
Data Security and Transparency
Transparency in algorithms, usage, and decision-making processes helps ethical access to data, building customers' trust in the business. Additionally, providing the option to quit or modify the type of data usage at any time gives freedom and a sense of control to the users, further taking actions to benefit both companies and themselves.
Regular assessments to seek vulnerable points in the data and network protection from major losses. Multiple easy-to-apply measures are available to safeguard the data. Businesses can opt to erase or encrypt personal identifiers to avoid connecting the information of individuals. Further, another method that is not reliable but comparatively effective is data anonymization.
Data Literacy and Awareness
Increasing awareness of data collection, storage, and usage to consumers is another method to help them make informed decisions. It should include unbiased information on benefits and harms imposed on either participant. Actions to take to avoid misuse of data or practices used by businesses to prevent the same are critical.
Businesses can practice ethical considerations when the leaders are ethically considerate. A change in mindset to value individuals’ privacy and respect their rights is an important and self-learnable task. Shielding behind ethical data usage to eventually use it to discriminate against other uninformed or unethical processes is ethically incorrect in itself. Self-awareness of actions is critical.
Alt-text: Best practices for ethical usage of Big Data
What Are the Benefits of Maintaining Big Data Ethics?
Ethical implications of Big Data helps to:
- Build a loyal and strong community of customers
- Enhances the trust of the consumers
- Earns unbiased and positive reviews from users and critics
- Increase efficiency of decision-making through the reliability of trustworthy and accurate data
- Decreases ethical dilemmas and requirements to perform unethical and immoral actions
- Enhances positive social impact on healthcare, education, and other sectors of society
Learning Big Data Ethics with Interview Kickstart
The generation of data has been significant since the introduction of the Internet. The accumulation nowhere seems to decrease but rather increases exponentially. Candidates seeking opportunities to exhibit their potential in big data privacy and ethics hold a strong position and future career aspects if they contribute their time and energy efficiently. Post learning the basics of the technology and focusing on the application of skills ethically, the candidates require presentation skills.
Helping them with it, Interview Kickstart harbors top recruiters from FAANG companies to train the candidates for interview processes. Knowing the expectations of leaders, they have trained millions of individuals to help them land their dream jobs. Learn more about their strategies from the webinar that is going to be conducted soon. You have the opportunity to register for the webinar for free and ask your queries face-to-face.
FAQs About Big Data Ethics
Q1. What are the challenges in using ethical Big Data?
The requirement of measures to validate the data accuracy and reliability, adopt Big Data technologies, and comply with data privacy regulations are the challenges and ethical issues with big data.
Q2. How do you collect data ethically?
Maintaining transparency by providing collector’s details, looking for their consent, eliminating information leading to physical or emotional harm, and remaining neutral and unbiased are some methods of ethical data collection.
Q3. What are the four elements of big data ethics?
Accountability, data privacy, transparency, and consent are four elements of big data ethics.
Q4. What are the principles of GDPR?
The five principles of the General Data Protection Regulation (GDPR) are: lawful processing of personal data, collection for explicit, specific, and legitimate purposes, limitation to necessity, regular updation and accuracy, processing in appropriate security, and data should be easily identifiable if necessary.
Q5. What are the three types of ethical issues?
The three main types of ethical issues are utilitarian, virtue, and deontological.
Q6. What are the 4 Cs of big data?
The four Cs of Big Data are customers, context, chaos, and cloud.
Q7. What are the examples of data ethics?