Data Science Ethics And Its 5 Principles For Businesses

Terms of use

Terms of Use

The use of this site and the content contained therein is governed by the Terms of Use. When you use this site you acknowledge that you have read the Terms of Use and that you accept and will be bound by the terms hereof and such terms as may be modified from time to time.

All text, graphics, audio, design and other works on the site are the copyrighted works of nasscom unless otherwise indicated. All rights reserved.
Content on the site is for personal use only and may be downloaded provided the material is kept intact and there is no violation of the copyrights, trademarks, and other proprietary rights. Any alteration of the material or use of the material contained in the site for any other purpose is a violation of the copyright of nasscom and / or its affiliates or associates or of its third-party information providers. This material cannot be copied, reproduced, republished, uploaded, posted, transmitted or distributed in any way for non-personal use without obtaining the prior permission from nasscom.
The nasscom Members login is for the reference of only registered nasscom Member Companies.
nasscom reserves the right to modify the terms of use of any service without any liability. nasscom reserves the right to take all measures necessary to prevent access to any service or termination of service if the terms of use are not complied with or are contravened or there is any violation of copyright, trademark or other proprietary right.
From time to time nasscom may supplement these terms of use with additional terms pertaining to specific content (additional terms). Such additional terms are hereby incorporated by reference into these Terms of Use.

Disclaimer

The Company information provided on the nasscom web site is as per data collected by companies. nasscom is not liable on the authenticity of such data.
nasscom has exercised due diligence in checking the correctness and authenticity of the information contained in the site, but nasscom or any of its affiliates or associates or employees shall not be in any way responsible for any loss or damage that may arise to any person from any inadvertent error in the information contained in this site. The information from or through this site is provided "as is" and all warranties express or implied of any kind, regarding any matter pertaining to any service or channel, including without limitation the implied warranties of merchantability, fitness for a particular purpose, and non-infringement are disclaimed. nasscom and its affiliates and associates shall not be liable, at any time, for any failure of performance, error, omission, interruption, deletion, defect, delay in operation or transmission, computer virus, communications line failure, theft or destruction or unauthorised access to, alteration of, or use of information contained on the site. No representations, warranties or guarantees whatsoever are made as to the accuracy, adequacy, reliability, completeness, suitability or applicability of the information to a particular situation.
nasscom or its affiliates or associates or its employees do not provide any judgments or warranty in respect of the authenticity or correctness of the content of other services or sites to which links are provided. A link to another service or site is not an endorsement of any products or services on such site or the site.
The content provided is for information purposes alone and does not substitute for specific advice whether investment, legal, taxation or otherwise. nasscom disclaims all liability for damages caused by use of content on the site.
All responsibility and liability for any damages caused by downloading of any data is disclaimed.
nasscom reserves the right to modify, suspend / cancel, or discontinue any or all sections, or service at any time without notice.

For any grievances under the Information Technology Act 2000, please get in touch with Grievance Officer, Mr. Anirban Mandal at data-query@nasscom.in.

New

See all

No notification found.

Data Science Ethics And Its 5 Principles For Businesses

keerthi reddy

@keerthireddy

September 29, 2022

Data Science & AI Community

230

Overview

Making decisions based on data can have a significant impact on businesses. Nevertheless, there are some disadvantages to this beneficial resource. What ethical means can businesses collect, store, and use data? What rights are necessary to safeguard? Personnel in business who handle data must adhere to certain ethical standards. There must be a proper way to use the data and maintain privacy because data is someone's personal information.

Ethics

The Greek word ethos, which means "habit" or "custom," is where the word "ethics" originates. Ethics teaches us the difference between right and wrong. Philosophers have debated this important issue for a very long time, and they have much to say about it. Most people link morality, or a sense of what is "good," to ethics. Humans live in societies, and societies have laws and rules. We must be able to differentiate between right and wrong. Ethics is concerned with the emotions, rules, and social norms that distinguish right and wrong. Our way of life must be reasonable and in line with social norms.

Why Is Ethics in Data Science Important?

Data science is now impacting how industries like medical sciences, smart cities, and transportation conduct business. The risks of data science without ethical considerations are as evident as ever, whether it's the protection of personally identifiable information, implicit bias in automated decision-making, the appearance of free will in psychographics, the social effects of automation, or the apparent separation of truth and trust in virtual communication. Because data science practices threaten our conception of what it means to be human, the need for a focus on data science ethics goes beyond a summary of these potential issues.

When used properly, algorithms have a great deal of potential to improve the world. The advantages could be enormous when we use them to carry out tasks that previously needed a person: cost savings, scalability, speed, accuracy, and consistency, to name a few. Additionally, the results are more balanced and less likely to exhibit social prejudice because the system is more accurate and dependable than humans.

Data Science Ethics

Data science ethics must concern analysts, data scientists, and IT professionals. Anyone who works with data must be familiar with the basics. Anyone working with any data type must report any instance of data theft, unethical data collection, storage, use, etc.

In the past, protected data has been posted online and made public, harming the people whose information was exposed. Data leaks can result from improperly configured databases, spyware, theft, or publication on a public forum. To address computer and data security, individuals and organizations must adopt safe computing practices, conduct regular system audits, and adopt policies. In order to prevent the leakage of data and information, businesses must implement the necessary cybersecurity measures. This is crucial for banks and other financial institutions that deal with customers' money. Policies require that protections be kept in place even when equipment is transferred or discarded.

5 Key Principles of Data Science Ethics

Making Decisions

Even if the decision is in the project's best interest, data scientists should never make decisions without first consulting the client. Both data scientists and clients need to be aware of the project's goals and objectives.

Let's imagine that a data scientist wants to act for a client on a specific ongoing project. Even if the decision is in the client's and the project's best interests, it must be made with their knowledge and consent. Data scientists make decisions when it is specifically stated in the contract or within the scope of their authority.

Privacy and Confidentiality of Data:

Data scientists are constantly involved in information creation, development, and acquisition. This category frequently includes information about client affiliates, customers, employees, or other parties with whom the clients have a confidentiality agreement. The data scientist must then take care to protect any sensitive information, regardless of the type. This type of information should only be disclosed or discussed when the customer gives consent for it to be done so. Data about clients or customers must be kept completely private.

Even if a customer gives permission for your business to gather, store, and analyze their personally identifiable information (PII), it doesn't necessarily follow that they want it to be made public.

Data Ownership:

The idea that each person has ownership over their data is one of the key ethical principles in data science. It is illegal and immoral to collect someone's personal information without their consent. As a result, permission is needed in order to obtain someone's data.

The typical methods for obtaining consent include:

Signed written agreements.
Digital privacy policies ask users to agree to a company's terms and conditions.
Pop-up windows with checkboxes that permit websites to track users' online activity using cookies.

Never assume a customer agrees to you collecting their data; always ask permission to avoid ethical and legal problems.

Good intentions with data:

Data collection and analysis must be done with good intentions. Data experts must be transparent about the purposes for which they use the data. The goal is good if a team gathers information on users' spending patterns to create an app for budgeting.

Transparency:

In addition to having a right to own their personal information, data subjects have a right to know how they intend to collect, store, and use it. When gathering data, transparency should be used. In addition to developing a policy outlining how cookies are used to track user activity and how the data collected is stored in a secure database, you should also develop an algorithm that provides a customized online experience. Users have a right to access this data to decide whether to accept cookies from your website.

Conclusion

Data science ethics is a crucial topic for debate in the modern world. Companies and organizations using data must adhere to certain ethical standards when working with it. Data can assist you in making better decisions and changing the world if used ethically. Wondering how to learn data science and its tools?

Data Science data science course in Pune data analytics course in pune Data Science Ethics And Its 5 Principles For Businesses

Disclaimer

That the contents of third-party articles/blogs published here on the website, and the interpretation of all information in the article/blogs such as data, maps, numbers, opinions etc. displayed in the article/blogs and views or the opinions expressed within the content are solely of the author's; and do not reflect the opinions and beliefs of NASSCOM or its affiliates in any manner. NASSCOM does not take any liability w.r.t. content in any manner and will not be liable in any manner whatsoever for any kind of liability arising out of any act, error or omission. The contents of third-party article/blogs published, are provided solely as convenience; and the presence of these articles/blogs should not, under any circumstances, be considered as an endorsement of the contents by NASSCOM in any manner; and if you chose to access these articles/blogs , you do so at your own risk.

keerthi reddy

Key Trends in Gen AI Startups: Pivo...

Madhumay

Digital Transfo..

15 Nov 2024

Power of Machine Learning via Data ...

Snowflake

Machine Learnin..

15 Nov 2024