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Certified Ethical Emerging Technologist

The CertNexus® Certified Ethical Emerging Technologist™ (CEET) is designed for individuals seeking to demonstrate a vendor neutral, cross-industry, and multidisciplinary understanding of applied technology ethics that will enable them to navigate the processes by which ethical integrity may be upheld within emerging data-driven technology fields (such as artificial intelligence (AI)/machine learning, Internet of Things (IoT), and data science).



Certified Ethical Emerging Technologist

The CertNexus® Certified Ethical Emerging Technologist™ (CEET) is designed for individuals seeking to demonstrate a vendor neutral, cross-industry, and multidisciplinary understanding of applied technology ethics that will enable them to navigate the processes by which ethical integrity may be upheld within emerging data-driven technology fields (such as artificial intelligence (AI)/machine learning, Internet of Things (IoT), and data science).

Certified Ethical Emerging Technologist Jobs


  • Policy, Compliance, Regulatory, Governance Lead/Manager or Officer
  • Data Analyst
  • Data Scientist
  • Data Architect
  • Data Engineer
  • Business Analyst
  • AI Engineer
  • Machine Learning Developer
  • Product Manager
  • UX Designer
  • Technology Consultants
  • Data Protection Officer
  • Quality and Risk Management Lead
  • Software Systems Architect
  • Software Solutions Architect
  • System Administrator
  • Security Analyst
  • Procurement Officer
  • Public Relations/Communications Manager
  • Management Consultants
  • Data Journalist





CEET Exam Details

This exam will certify that the successful candidate has the knowledge, skills, and abilities required to apply foundational ethical principles, follow industry-standard frameworks, identify and mitigate risks, and navigate ethical organizational governance in order to devise and maintain ethical, trusted, and inclusive data-driven technologies.



TARGET CANDIDATE

This certification exam is designed for individuals seeking to demonstrate a vendor neutral, cross-industry, and multidisciplinary understanding of applied technology ethics that will enable them to navigate the processes by which ethical integrity may be upheld within emerging data-driven technology fields (such as artificial intelligence (AI), Internet of Things (IoT), and data science).

EXAM CODES

CET-110


LAUNCH DATE

October 2020


SUNSET DATE

TBD


EXAM DURATION

120 minutes (Note: Published exam times include the 10 minutes you are allotted for reading and signing the Candidate Agreement and reviewing exam instructions.)

PASSING SCORE

62%


NUMBER OF ITEMS

80


ITEM FORMATS

Multiple Choice/Multiple Response


EXAM OPTIONS

In person at Pearson VUE test centers or online via Pearson OnVUE online proctoring







Why Get Certified Ethical Emerging Technologist Certified?

As organizations acquire extraordinary amounts of data and use the information learned from this data to understand their businesses processes, opportunities, audience, risks, and more, analyzing and applying these insights ethically has become critical.

REMOVE BIASES

It is critical that data is utilized ethically to avoid the perpetuation of biases.

CREATE ETHICAL FRAMEWORKS

The frameworks that organizations rely on must reconcile the needs of ethical duties and business practicalities.

DETECT AND MITIGATE RISKS

Ethical treatment of data requires that ethical risks in the design, development, and deployment of data-driven technologies be identified and mitigated.






Certified Ethical Emerging Technologist Training


CertNexus offers training to prepare individuals to earn the Certified Ethical Emerging Technologist (CEET). Using the tools and techniques covered in these courses, individuals will be empowered to remove biases, create ethical frameworks, and build organizational buy-in.







Course Details

1. Fundamental Concepts for Data-Driven Technology Ethics

  • Identify important to data-driven technology ethics
    • AI-related concepts
    • Data science-related concepts
    • Legal-related concepts
    • Privacy-related concepts
    • Ethics
    • Bias
    • Evaluation metrics
  • Identify and describe common ethical theories
    • Moral philosophy
    • Applied ethics
  • Identify when it is appropriate to conduct an ethical risk review
    • Ideation and innovation management activities
    • What-if scenario planning sessions
    • New product/service development
    • All along the data science/AI development lifecycle, from ideation and design through deployment and maintenance
    • Stage gates and other points as appropriate within an organization’s Ethics-by-Design practices
    • When legal and/or regulatory non-compliance has occurred
    • When an ethical violation or incident has occurred

  • Identify Major Ethical frameworks
    • Privacy
    • Accountability
    • Safety and Security
    • Transparency and Explainability
    • Fairness and Non-Discrimination
    • Human Control of Technology
    • Professional Responsibility
    • Promotion of Human Values
  • Identify and select an Ethical Framework to understand the issue
    • Initiatives
  • Follow applicable regulations, standards, and best practices
    • Regulations
    • Standards/best practices
  • Regulatory and/or business constraints or demands
    • Data minimization principle vs. need for data
    • Performance vs. explainability
    • Compliance vs. cost
    • Transparency/explainability vs. intellectual property rights
    • Company/stakeholder needs vs. ethical decision making
    • Ethics washing
    • Efficiency vs. the risk of collateral damage
    • Proliferation of AI to unscrupulous actors vs. democratization of AI (e.g., open source)
    • Efficiency of development vs. cultural/contextual sensitivity
    • Availability of datasets for ML algorithms vs. privacy protection
    • Big data generated through devices (cloud, IoT) vs. concentration of power in big tech
    • Fair competition vs. corporate hegemony (data assets)
    • Efficiency/streamlining experience vs. enabling human agency/autonomy
    • Moral relativism vs. evidence-based policy

  • Identify and mitigate privacy risks
    • Source
    • Methods of identification
    • Mitigation strategies
    • Tools for identification/mitigation
  • Identify and mitigate accountability risks
    • Source
    • Methods of identification
    • Mitigation strategies
    • Tools for identification/mitigation
  • Identify and mitigate transparency and explainability risks
    • Source
    • Methods of identification
    • Mitigation strategies
    • Tools for identification/mitigation
  • Identify and mitigate fairness and non-discrimination (bias) risks
    • Source
    • Methods of identification
    • Mitigation strategies
    • Tools for identification/mitigation
  • Identify and mitigate safety and security risks
    • Source
    • Methods of identification
    • Mitigation strategies (Security-by-Design practices)
    • Tools for identification/mitigation

  • Effectively communicate with key stakeholders and/or team members (internal communication)
  • Identified ethical risks
  • Business impacts
  • Business incentives
  • Marketing/Public Relations
  • Brand awareness/value
  • Media inquiries
  • Corporate reporting
  • Organizational philosophy
  • Disclosure statements

  • Identify Ethical organizational culture
    • Training
    • Leadership championing
    • Incentive structures
    • Culture-building workshops
    • Creation of an ethics board
    • Organizational resourcing
  • Identify Development, use, and governance of technology
    • Fair competition
    • Open data
    • Privacy
    • Intellectual property
    • Fairness
    • Non-discrimination
    • Legal and regulatory requirements
    • Human rights
    • Accountability
    • Transparency
    • Animal rights/welfare
    • Environmental concerns
    • Economic impacts
    • Workforce impacts
  • Developing a code of ethics
    • Identify internal and external stakeholders who should review or contribute
    • Determine your organization’s memberships in ecosystems, industry, and professional groups
    • Collect codes of ethics from the above groups and aggregate their codes as a minimum baseline for your own code
    • Consult with process owners to understand any factors which may frustrate or impede the adoption of more ethical practices
    • Publish draft among stakeholders who will participate in a pilot for a determined length of time
    • During the pilot period, interview stakeholders at predetermined intervals to understand impacts of change
    • Upon completion of the pilot, update and ratify the code of ethics
  • Developing an ethical organizational policy
    • Identify the need for the policy
    • Identify the owner(s) of the policy
    • Gather information about the policy
    • Draft the policy
    • Consult appropriate stakeholders
    • Approve and publish the policy
    • Establish procedures to support the policy
    • Implement the policy
    • Monitor and refresh the policy at regular intervals
  • Evaluate Internal and external ethical policies
    • Sentiment analysis of public discussion
    • Surveys and focus groups
    • Periodic health check of ethical policies
    • Number and severity of ethical violations
    • Industry best practices/leading best practices


Fees Structure : 22500 INR / 270 USD
Total No of Class : 72 Video Class
Class Duration : 42 Working Hours
Download Feature : Download Avalable
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

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Fees Structure : 30500 INR / 365 USD
Class Duration : 60 Days
Class Recording : Live Class Recording available
Class Time : Monday to Firday 1.5 hours per day / Weekend 3 Hours per day
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

Download Brochure       Pay Online