We seek to promote thoughtful collaboration and open dialogue about the potential subtle and salient influences of AI on people and society.
Good AI offers great potential for promoting the public good for example in the realms of education, housing, public health and sustainability
There are concerns about algorithms’ opacity the code of algorithms may be unviewable in systems that are proprietary or outsourced, even if viewable the code may be essentially uncheckable, if it’s highly complex where the code continuously changes based on live data or where the use of neural networks means that there is no single ‘point of decision making’ to view before data may go through...
Does your company communicate clearly, honestly and directly about any potential risks of the product or service you are providing what does it communicate?
We seek to promote thoughtful collaboration and open dialogue about the potential subtle and salient influences of AI on people and society.
Good AI offers great potential for promoting the public good for example in the realms of education, housing, public health and sustainability
There are concerns about algorithms’ opacity the code of algorithms may be unviewable in systems that are proprietary or outsourced, even if viewable the code may be essentially uncheckable, if it’s highly complex where the code continuously changes based on live data or where the use of neural networks means that there is no single ‘point of decision making’ to view before data may go through...
Does your company communicate clearly, honestly and directly about any potential risks of the product or service you are providing what does it communicate?
wikipedia
Ethics or moral philosophy is a branch of philosophy that involves systematizing, defending, and recommending concepts of right and wrong conduct.
...systematizing conduct.
(This is a working definition for this talk)
Ben Byford, Pydata London
(Why should we care?)
Jaron Lanier, You Are Not a Gadget
DigitalCatapult
Machine Intelligence Garage Ethics Committee
chaired by Luciano Floridi
Where do these decisions get made?
AI in Warfare, regulation of malpractise, best practise / investing in research, bad actors and security, democratisation of tools, educate or get left behind, using other companies algorithms are they ok, company acquisition, team diversity, what does success look like, impact on currently held freedoms e.g free speech, democracy, monopolies of algorithmic power, job displacement,
who is accountable, what is the visibility of that account, secrecy, how to implement and where, unintended consequences, can the users interpret the system, is it exploitative, false positives and true negatives, is the system designed dogmatically, what behaviours is the system promoting, discriminatory, how can the algorithm fail, does the system change over time and does it need to be repeatedly tested for changes, Is the output explainable - does it need to be, what bias do you have in the data,
do you have enough data to make descisions, Is the data reliable, is it appropriate, proper consents, Inference of anonymised personal data, what score / threshold is good for your domain?
OECD AI Principles
https://www.oecd.org/going-digital/ai/principles/
IBM - everyday ethics
https://www.ibm.com/watson/assets/duo/pdf/everydayethics.pdf
Digital catapult - machine intelligence garage,
Luciano Floridi
Projects by IF
Govenments -> Regulation(?), Sign-post good practise,
help us decide on basic principles for tech ethics and more.
Businesses -> hold themselves accountable,
create services in society's interest, expect unintended consequences
Designers / developers / data scientists -> Collaborate on ethical issues, whistleblow where human right obligations are not being met, make ethical thinking part of your process.
Research -> continued research on algorithmic ethical agents (machine ethics) which needs to be more transparent and less click baity (terminator / your car is going to kill you), and transparent algorithmic decision making
Much more...
Extra credits:
1. Hire us: www.ethicalby.design - talks, research, consultancy, workshops.
2. Create an AI governance group: designers, users, directors, data scientists, allow these people to "own" the process of scrutony for your projects... They're like AI fire wardens.
3. Risk assess your service / product against ethical issues and unintended consequences, use this to put processes and culture changes into place.
4. Revisit your AI processes, evalute them and keep up to date with new AI issues in data science and ML algorithms.
5. Publicily declare your intent, processes and updates... you don't have to give up your secret source just give us as much as possible to be able to see your doing well.
Samuel Johnson
Anderson, Anderson 2012
NOTES