Answers.Body: <p>The current version of the document <a href="https://www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology/initial-code-of-conduct-for-data-driven-health-and-care-technology#principle-7-show-what-type-of-algorithm-is-being-developed-or-deployed-the-ethical-examination-of-how-the-data-is-used-how-its-performance-will-be-validated-and-how-it-will-be-integrated-into-health-and-care-provision" rel="nofollow noreferrer">Code of conduct for data-driven health and care technology</a> provides more details about all principles, including principle number 7, which I will quote here.</p>
  <blockquote>
  <p>Consider how the introduction of AI will change relationships in
  health and care provision, and the implications of these changes for
  responsibility and liability. Use current best practice on how to
  explain algorithms to those taking actions based on their outputs.</p>
  <p>When building an algorithm, be it a stand-alone product or integrated
  within a system, show it clearly and be transparent of the learning
  methodology (if any) that the algorithm is using. Undertake ethical
  examination of data use specific to this use-case. Achieving
  transparency of algorithms that have a higher potential for harm or
  unintended decision-making, can ensure the rights of the data subject
  as set out in the Data Protection Act 2018 are met, to build trust in
  users and enable better adoption and uptake.</p>
  <p>Work collaboratively with partners, specify the context for the
  algorithm, specify potential alternative contexts and be transparent
  on whether the model is based on active, supervised or unsupervised
  learning. Show in a clear and transparent specification:</p>
  <ul>
  <li>the functionality of the algorithm</li>
  <li>the strengths and limitations of the algorithm (as far as they are known)</li>
  <li>its learning methodology</li>
  <li>whether it is ready for deployment or still in training</li>
  <li>how the decision has been made on the acceptable use of the algorithm in the context it is being used (for example, is there a
  committee, evidence or equivalent that has contributed to this
  decision?)</li>
  <li>the potential resource implications</li>
  </ul>
  <p>This specification and transparency in development will build trust in
  incorporating machine-led decision-making into clinical care.</p>
  </blockquote>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-07-15T12:29:04.330Z
Answers.LastActivityDate: 2020-07-15T12:29:04.330Z
Answers.UserDisplayName: nbro
Body: <p>The <a href="https://www.gov.uk/health-and-social-care/national-health-service" rel="nofollow noreferrer">National Health Service (NHS)</a> wrote down several principles in a document <a href="https://www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology/initial-code-of-conduct-for-data-driven-health-and-care-technology" rel="nofollow noreferrer">Code of conduct for data-driven health and care technology</a> (updated 18 July 2019). I am concerned with principle 7.</p>
  <blockquote>
  <h3>Show what type of algorithm is being developed or deployed, the ethical examination of how the data is used, how its performance will be validated and how it will be integrated into health and care provision</h3>
  <p>Demonstrate the learning methodology of the algorithm being built.
  Aim to show in a clear and transparent way how outcomes are validated.</p>
  </blockquote>
  <p>But how exactly can outcomes be shown in a clear and transparent way how outcomes are validated?</p>
  
Tags: <social><ethics><healthcare>
Title: How can it be shown clearly and transparently that the outcomes of data-driven health and care technology are validated?
UserDisplayName: benbyford
ThreadText: # How can it be shown clearly and transparently that the outcomes of data-driven health and care technology are validated?
  
  (Asked by: username_0 on 2019-02-20)
  
  The [National Health Service (NHS)](https://www.gov.uk/health-and-social-care/national-health-service) wrote down several principles in a document [Code of conduct for data-driven health and care technology](https://www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology/initial-code-of-conduct-for-data-driven-health-and-care-technology) (updated 18 July 2019). I am concerned with principle 7.
  
  > ### Show what type of algorithm is being developed or deployed, the ethical examination of how the data is used, how its performance will be validated and how it will be integrated into health and care provision
  >
  > Demonstrate the learning methodology of the algorithm being built.
  > Aim to show in a clear and transparent way how outcomes are validated.
  
  But how exactly can outcomes be shown in a clear and transparent way how outcomes are validated?
  
  **Tags:** social, ethics, healthcare
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-07-15. Score: 0
  
  The current version of the document [Code of conduct for data-driven health and care technology](https://www.gov.uk/government/publications/code-of-conduct-for-data-driven-health-and-care-technology/initial-code-of-conduct-for-data-driven-health-and-care-technology#principle-7-show-what-type-of-algorithm-is-being-developed-or-deployed-the-ethical-examination-of-how-the-data-is-used-how-its-performance-will-be-validated-and-how-it-will-be-integrated-into-health-and-care-provision) provides more details about all principles, including principle number 7, which I will quote here.
  
  > Consider how the introduction of AI will change relationships in
  > health and care provision, and the implications of these changes for
  > responsibility and liability. Use current best practice on how to
  > explain algorithms to those taking actions based on their outputs.
  >
  > When building an algorithm, be it a stand-alone product or integrated
  > within a system, show it clearly and be transparent of the learning
  > methodology (if any) that the algorithm is using. Undertake ethical
  > examination of data use specific to this use-case. Achieving
  > transparency of algorithms that have a higher potential for harm or
  > unintended decision-making, can ensure the rights of the data subject
  > as set out in the Data Protection Act 2018 are met, to build trust in
  > users and enable better adoption and uptake.
  >
  > Work collaboratively with partners, specify the context for the
  > algorithm, specify potential alternative contexts and be transparent
  > on whether the model is based on active, supervised or unsupervised
  > learning. Show in a clear and transparent specification:
  >
  > * the functionality of the algorithm
  > * the strengths and limitations of the algorithm (as far as they are known)
  > * its learning methodology
  > * whether it is ready for deployment or still in training
  > * how the decision has been made on the acceptable use of the algorithm in the context it is being used (for example, is there a
  >   committee, evidence or equivalent that has contributed to this
  >   decision?)
  > * the potential resource implications
  >
  > This specification and transparency in development will build trust in
  > incorporating machine-led decision-making into clinical care.
  
  
  ---
  
  