ETHICBOTS “crude” questions

(how) is the ICT monitoring and use

of personal data to be regulated?

who is responsible for actions carried

out by human-robot hybrid teams?

can bionic implants be used to

enhance physical and intellectual

capabilities?

concerning human-machine integration

Human-softbot integration, as achieved by AI research on information and communication technologies;

Human-robot, non-invasive integration, as achieved by robotic research on autonomous systems inhabiting human environments;

Human-robot invasive integration, as achieved by bionic research.

ETHICBOTS Strategic objectives

Raising awareness and deepening understanding of these techno-ethical issues (conceptual analysis);

Ethical monitoring of ICT, robotic, and bionic technologies for enhancing human mental and physical capacities;

Fostering integration between Science and Society, by promoting responsible research, providing input to EU and national

committees for ethical monitoring, warning, and opinion generation,

improving communication between scientists, citizens and special groups.

Multiple-actor enterprise

Ordinary citizens

Legal experts

Computer

scientists

Sociologists

Roboticists

Philosophers

Theologians

……………………

…

Conceptual analysis by experts

• Conceptual analysis on the basis of specialized knowledge

• triaging techno-ethical issues, • deepening our understanding of the

higher-ranked issues, • identifying ethical motivations opening

new research perspectives,• dispelling misconceptions

Triaging: identifying potential impact categories

We need a set of Potential Impact Categories (PICs) as a basis for triaging emerging techno-ethical issues.

Examples: imminence, novelty, Social pervasiveness of technologies.

General Ethical Themes

Personal integrity and identity

Responsibility Autonomy Fair access

Deepening our understandinglearning machines and responsibility

Designers, manufacturers, and operators cannot fully predict the behaviour of many learning machines based on

symbolic learning

neural network learning

evolutionary algorithmsTraditional concepts of responsibility ascription fail!

Deepening our understandingBeing cautious about precautionary

principles

Should one enforce a “human-in-the-control-loop” exceptionless requirement?

No! Machines can take decisions which humans should not override (e.g., to prevent accidents)

Ethically motivated research

Improving machine learning standards

Practising cooperative design

Providing machines with explanation &

justification facilities

Explanation and justification

Accountability, autonomy, trust, social anxiety

Machines should become increasingly capable to explain and justify their courses of action

Antecedents in knowledge-based decision support systems and expert systems

Future Developments: Machine introspective and reflective capacities

Dispelling misconceptions

“The machine will do exactly what we

programmed it to do…”

Do we fully understand the robots we make

and theorize about?

Can we fully predict and control robot

behaviour?

Misconceptions at war

The American military is working on a new generation of soldiers, far different from the army it has. "They don't get hungry," said Gordon Johnson of the Joint Forces Command at the Pentagon. "They're not afraid. They don't forget their orders. They don't care if the guy next to them has just been shot. Will they do a better job than humans? Yes.“ The robot soldier is coming.

Front-page article, NYT 16 feb. 2005 T. Weiner

Robo-soldiers & AI-complete problems

Open context interpretation

Recognizing surrender gestures

Telling bystanders from foes