Data Ethics: Concepts, Best Practices, Issues

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Data Ethics: Concepts,

Best Practices, Issues

Webinar Series: Data Management Mastery

Anne Marie Smith, Ph.D.

VP of Education, Chief

Methodologist

EWSolutions

[email protected]

mailto:[email protected]





ETHICS – CONCEPTS AND QUESTIONS





Every Organization Has Data – and Challenges





Ethics, Data, and Organizations

❑ Data and its use in every industry has come under harsh review

❑ Variety of federal and local laws – in all locations - are under

consideration to control the collection, sale, and use of data

❑ American companies and legislatures working to match the

tougher privacy regulations already in place in Europe and

other regions

❑ Personal and class-action litigation against businesses over

data-privacy issues is increasing





Thinking About Ethics

❑ Ethics: well-founded standards of right and wrong that

prescribe what humans ought to do, usually in terms of rights,

obligations, benefits to society, fairness, or specific virtues

❑ Ethical decisions have various consequences, outcomes,

alternatives and personal implications

❑ Both law and ethics are applicable to all walks of life and to all

professions





Law versus Ethics

❑ Law is a set of rules that are framed,

accepted and usually enforced

➢ Definition of law contains terms such as

consistent, universal, published, accepted

and enforced

❑ Ethics define how individuals prefer to

interact with one another

➢ “Ethos” = “character” and “mores” =

“customs”

➢ Ethics cannot be compelled, cannot be

enforced and are not universal





Compliance vs. Ethics

❑ Compliance: accepting and following a set of rules, specified

in law, regulation, or professional codes of conduct

❑ Ethics: “knowing the difference between what you have a

right to do and what is right to do.” (US Supreme Court Justice

Potter Stewart)

❑ Many organizations develop a code of ethics and general

principles to mitigate risk of non-compliance

➢ Inclusive and non-discriminatory

➢ Honest and trustworthy





DATA ETHICS

Strategic Partner & Systems Integrator

Intelligent Business Intelligencesm





Data Ethics Definition

❑ Data Ethics : a code of behavior that describes

what is acceptable vs. unacceptable in:

➢ Data acquisition, generation, collection, usage,

dissemination, etc.

➢ Application of data in algorithms and models, artificial

agents, machine learning, robotics, etc.

➢ Operations, including programming, hacking,

research and development, etc.

❑ Usually based, in part, on the organization’s

general code of behavior, general code of ethics,

etc.





Reasons to Care about Data Ethics

❑ Data is powerful and can be used

for good in every organization

❑ With great power comes great

responsibility

❑ The line between what is a good

use of data and what is a bad use

of data is both thin and blurry

❑ We live in an online world, and

everyone is affected by using

data in all its formats





Data Ethics: People, Process, Technology, Data

❑ People, process, technologies, and data

are aspects of an effective data ethics

policy – and its implementation

❑ Lose one aspect and the ability to maintain

an ethical data environment is lost





A business issue? A technology issue?

❑ Business staff may not be aware of “where the data comes from” and ethical issues may not be obvious to them

❑ Automated monitoring is not sufficient protection for ethical data collection and use

❑ Cultural norms and ethics in the workplace influence corporate behavior

❑ Organizations have not addressed the need for data management, so there is little focus on data management and data governance, including ethical treatment of data

❑ Regulations are not sufficient to prevent unethical behavior

Ethics in Data Management is a human issue

Ethics in Data Management





Data Professionals and Ethics

❑Data professionals in all industries have a duty to govern and work with data ethically

❑Business and IT data professionals should resist requests / demands for unethical or improper data practices

➢ What is “unethical” or “improper”?

❑Data management professionals should create and implement a data management ethics code for their organization

❑Data governance at all levels is essential for supporting corporate ethics / principles in data management





DATA ETHICS ISSUES, CODES,

PRINCIPLES, POLICIES







Ethics Principles, Codes, Policies

Business and data

management leaders

develop codes, set and

maintain policies, direct

implementations of

ethical practices – all

based on principles

Codes, principles,

policies, and

procedures must

be socialized

throughout

organization

Principle: fundamental assumption

Code: a set of rules that serve as generally accepted

guidelines recommended to be followed, often based

on principles

Policy: formal statements produced and supported

by senior management (implemented by procedures)





Ethical Issues in Data Management

❑ Fundamental Issues in Data Quality and Data Usage

➢ Integrity and trust in data (captured, stored, used)

❑ Support for Operational and Decision-Making Capabilities

➢ Protecting source data for validity and other characteristics, ability to

aggregate appropriately for decision support

❑ Compliance and Governance Issues

➢ Data collection and usage must comply with all laws (international,

federal and state), regulations, fiscal and monetary reporting statutes

and all applicable civil rights laws, including privacy and security





Uses of Data Ethics in Organizations

Comply with

regulations –

reduce or

eliminate fines

and penalties

Prove the

organization is

trustworthy with

customers’ data

Ensure fair and

reasonable data usage

in its operations and

decisions

Minimize biases and social

inequities to improve

equitable approach to

customers and communities

Develop a positive

public perception to

enhance reputation

and increase market

share

Improve data and

information security

processes and define

roles / responsibilities





Common Principles of Data Ethics

Transparency of data collection and use purposes

– from the start

Accountability for actions, for decisions, etc.

Establishing, understanding, and enforcing organizational

conformance to data policies, standards, architecture, and

procedures

Managing and resolving data privacy / data security

related issues, and reporting results

Using data for stated purposes only – beneficial

for all involved parties

Designing and using algorithms free from bias

and assumptions





Common Data Ethics Challenges

Data and information

control, and monitoring

vs. managing privacy

expectations and

restricting use

Accuracy of data and

information quality –

limitations and need for

accuracy – data bias

User expectations,

user accountability

and responsibility,

interaction with

organization

Data privacy,

availability and

usage, data

accessibility

Data ownership and

stewardship, non-

disclosure rights, general

knowledge vs. “need to

know”, organizational

accountability

Security – data and

technology – liability

for incidents –

breach notifications

– supporting privacy





Themes to Facilitate Data Ethics Discussion

Examining data –review

practices for collecting,

storing, distributing data

appropriately

Questions and

problems identifying

valuable and relevant

issues for data

collection and use

Revising / updating

algorithms and

models to remove

bias and

assumptions

Identifying existing

resources for best

practices in data

management and data

usage

Fostering welcoming

community for data

management, ethical

treatment of people,

processes, and data

Reviewing

technology. and its

challenges and

benefits





STEPS AND ACTIONS TO DEVELOP

DATA ETHICS, ETHICAL RISKS







Considerations for Ethical Data Use

Regularly

review data

governance

polices to

ensure

attention to

data ethics

Respect persons

behind data – do no

harm with data

Be aware of downstream

use of data and data sets –

separate use consent

Only collect data

purposefully

Audit / track data

collection and usage –

operations and analytics

Include ethical practices

with audits and ensure

accountability

Maximize

transparency in data

collection and usage

Understand laws

and regulations –

avoid complacency





Steps to Develop an Ethical Culture for Data

Develop Organizational

Vision Statement

Create Organizational

Values Statement

Design Organizational Code

of Ethics

Create Code of Data Ethics – based on

Organizational Ethics Code

Appoint Ethics Officer and Ethics

Committee – include Data Management

and Analytics

Design and Implement Ethics Communication

Strategy

Design and Implement Ethics

Socialization Strategy

Develop and Implement Ethics Training – include Data Management

and Analytics

Measurement, Monitoring,

Rewards, Penalties





Some Examples of Ethical Risks with Data

❑ Data aggregation and reconstitution➢ Can create bias or present results that adhere to a pre-determined hypothesis

❑ Data Profiling➢ Should not be performed to support pre-determined hypotheses or omit data that show

results not desired

❑ Biased data collection and use➢ Do not only collect data that supports desired results, nor only present data that supports

desired conclusions. Review algorithms and models to remove bias

❑ Data cleaning and standardization➢ Cleansing must be done according to established and consistent business rules,

governance must be enforced by business and enabled by technology

❑ International movement of personal data➢ Laws may prevent movement of some data, attempts to subvert for “business” reasons

can have serious implications

❑ Information dissemination within and across companies➢ Information security is an ethical concern as well as legal and technical concern





Actions to Avoid for Ethical Data Usage

Do not use information to

support actions that could

allow individuals to profit

Do not engage in

"administrative

voyeurism”

Do not choose data to

support a pre-

determined outcome

for analysis (avoid

bias)

Do not provide access to

data sets that are

broader than those

available to the

requestor via their own

approved access levels

Do not disclose

information about

individuals without

prior appropriate

authorization





Data Ethics Requires Cultural Change

Development of

data strategy

including ethical

data usage

Implementation of

corporate data

ethics policies

Hiring, retaining data

management and data

governance professionals

aligned with organizational

approach to data ethics

Embedding data ethics into

the organization, through

the business

Adopting effective

data stewardship

for improved,

ethical use of data

Identifying critical success

factors, failure reasons,

business case opportunities,

and challenges for advancing

ethical culture of data

management

Educating leadership and

staff on data ethics, role of

data governance and data

stewardship in advancing

ethical data culture





❑ Data Ethics is an emerging topic➢ Data is created at increasing speeds, use of algorithms and models is

exploding

➢ Without data ethics, difficult to manage data collection, usage, dissemination, and comply with laws and regulations

➢ Big Data, data science and advanced analytics all require an enterprise approach to data ethics

❑ Treating data collection, usage, dissemination is right thing to do➢ Unethical behavior exposes organizations and individuals to damage

❑ Enacting Data Ethics has many benefits – and many challenges➢ Realizing benefits and overcoming challenges is a journey

➢ Ask the right questions, be consistent in approaches, socialize proper data ethics and practices

Key Learning Points





Questions





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Enterprise Warehousing Solutions, Inc.

© 2017 All Rights Reserved

Anne Marie Smith, Ph.D., CDMP

VP of Education, Chief

Methodologist

EWSolutions, Inc.

[email protected]://www.linkedin.com/in/annemariesmith

Contact



https://www.linkedin.com/in/annemariesmith




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Data Ethics: Concepts, Best Practices, Issues