[SystemSafety] AI and the virtuous test Oracle - action now!

[Martyn Thomas]

Those who create risks should be required to control them adequately and to provide evidence that they have done so effectively. AI doesn’t change that. 

Regards

Martyn

> On 27 Jun 2023, at 05:53, Steve Tockey <steve.tockey at construx.com> wrote:
> 
> 
> Les,
> 
> “silicon is unbounded”
> 
> I disagree. Silicon is bounded, just in different ways than humans. For one, Turing Computability. Turing Machines, which all modern silicon computers are a kind of, are 100% deterministic. Human intelligence is non-deterministic. Thus, I argue, human intelligence is not something that a computer could ever actually be capable of. See, for example:
> 
> https://youtu.be/i2trJEIFIvY
> 
> I agree that, “We are embarked; we need to deal with it”. But we also have to be aware of the limits of so-called AI.
> 
> 
> — steve
> 
> 
> 
>> On Jun 26, 2023, at 9:15 PM, Les Chambers <les at chambers.com.au> wrote:
>> 
>> Hi
>> 
>> I put it to you and the list in general, a "discuss later" mentality is foolish 
>> in the extreme. The process of deploying intelligence in automated systems has 
>> , and will,  fundamentally change. Among other things, international bodies 
>> that currently regulate software-intensive Safety-Critical systems - who cling 
>> to regulating processes that have ceased to exist - are likely to be overrun 
>> and made redundant. 
>> 
>> In favour of organisations such as:
>> 
>> - The Center for Human-Compatible AI at UC Berkeley
>> - The Future of Life Institute
>> - The Center for AI Safety (CAIS)
>> - Stanford Center for AI Safety
>> 
>> My view is that this is not a steady-as-she-goes situation. This is a major 
>> inflection point in the evolution of intelligence. Carbon hosts will always be 
>> limited; silicon is unbounded. We are embarked; we need to deal with it.
>> 
>> Suggested reading: Max Tegmark, Life 3.0
>> 
>> Les
>> 
>> C2 - Confidential
>> 
>> Hello,
>> 
>> For the moment, I don't see in industry any attempt to realise E/EPE safety 
> related function with On-line AI. All what I see is focused on off-line AI, 
> meaning that the training is done specified training data sets, and the 
> validation is done on specified test datasets. We don't see any performance 
> better than roughly 3.3 10-3 in automotive. So let's wait for the achievement 
> of 10-8 to 10-5 error rate on test datasets and discusss later the 
> acceptability.
>> 
>> Attention : due to increased cybersecurity screening I may receive external 
> emails 30 minutes after their emission.
>> RESTRICTED
>> 
>> Bertrand RICQUE
>> Safety and security standardisation Expert
>> Program Support Manager
>> Optronics and Defence Division/Customer Support 
>> Safran Electronics & Defense 
>> 
>> P +33 (0)1 58 11 96 82   M +33 (0)6 87 47 84 64 
>> bertrand.ricque at safrangroup.com
>> 102 Avenue de Paris
>> 91300 MASSY FRANCE 
>> www.safran-electronics-defense.com 
>> 
>>> -----Message d'origine-----
>>> De : Les Chambers <les at chambers.com.au>
>>> Envoyé : lundi 26 juin 2023 06:03
>>> � : RICQUE Bertrand (SAFRAN ELECTRONICS & DEFENSE)
>>> <bertrand.ricque at safrangroup.com>; les at chambers.com.au;
>>> koopman.cmu at gmail.com; systemsafety at lists.techfak.uni-bielefeld.de
>>> Objet : RE: [SystemSafety] AI and the virtuous test Oracle
>>> 
>>> CAUTION:  This message originated from an outside organization. In case of
>>> suspicion, click on "Report to SAFRAN Security" from the Outlook ribbon.
>>> 
>>> RE your comment: â?oas it impossible, by construction, to identify all 
> dangerous
>>> situations�
>>> 
>>> True. But it is possible to identify the subset of highest probability
>>> â?odangerous situationsâ? and deal with them.  I had 10 years of 
> experience
>>> with this issue in computer control of chemical processing reactors. In the
>>> 1970s, we had a safety authority write software to: 1. identify well-
>>> established dangerous states of a reactor; 2. Transition reactor to a safe 
> state
>>> â?" usually shut down. It was called the â?oabortâ? programming. This 
> abort code
>>> overrode the control software written by another team. By today's standards
>>> it was primitive but still very effective.
>>> This experience has influenced my thinking on ways and means of dealing
>>> with â?obadâ? or â?ohallucinatingâ? AIs. We need a separate and distinct 
> â?oabortâ? AI
>>> capable of recognising evil and dealing with it.
>>> Sal Khan (Khan Academy) has implemented another idea in creating his
>>> Khanmigo personal tutor. To improve its accuracy in mathematics, he allows
>>> the AI to have â?opersonal thoughtsâ?. The AI equivalent of mindfulness
>>> (straight out of Marcus Aurelius). He gives the impression that he feeds 
> back
>>> the AI's response to the AI, so the AI can have a think about what it is
>>> thinking. A bit like briefing a fish on the concept of water.
>>> 
>>> This supports my pitch for engineers to be taught philosophy. The concepts
>>> of virtue and evil were defined simply 2000 years ago. These definitions 
> have
>>> stood outside of time and can be implemented with appropriate pattern
>>> matching.
>>> If Marcus Aurelius was reincarnated, he'd be running international seminars
>>> on mindfulness. The foundation ideas have not changed a wit.
>>> 
>>> Cheers
>>> Les
>>> 
>>> 
>>> 
>>>> C2 - Confidential
>>>> 
>>>> Answer to the first question. Once the NN is trained, it will always
>>>> give the
>>> same output for the same input. It is stupid software logic.
>>>> 
>>>> Answer to the second question. The current safety paradigm is based on
>>> perception-interpretation-decision-action loops based on the fact that:
>>>> 1 Either, all states of the system, leading to all identified losses,
>>>> can be
>>> exhaustively defined and their probability of occurrences remains, by
>>> concept and construction of the system, below a tolerable level, enabling
>>> fully autonomous functions (e.g. emergency shutdown functions in process
>>> industries),
>>>> 
>>>> 2 Or, there is a human in control of the system with the ability of
>>> arbitrating the decisions, meaning the ability to at least perceive and
>>> interpret.
>>>> 
>>>> AI deceives point 1 as it impossible, by construction, to identify all
>>> dangerous situations (the training dataset is incomplete and whatever its
>>> size, the operational domain being infinite (or close to infinite from a 
> practical
>>> point of view), training dataset size divided by infinite = 0.
>>>> 
>>>> To deceive the second assumption, just replace a car windscreen by a
>>>> video
>>> screen. No need of AI.
>>>> 
>>>> AttentionÃ, : due to increased cybersecurity screening I may receive
>>>> external
>>> emails 30 minutes after their emission.
>>>> RESTRICTED
>>>> 
>>>> Bertrand RICQUE
>>>> Safety and security standardisation Expert Program Support Manager
>>>> Optronics and Defence Division/Customer Support Safran Electronics &
>>>> Defense
>>>> 
>>>> P +33 (0)1 58 11 96 82   M +33 (0)6 87 47 84 64
>>>> bertrand.ricque at safrangroup.com
>>>> 102 Avenue de Paris
>>>> 91300 MASSY FRANCE
>>>> https://urldefense.com/v3/__http://www.safran-electronics-
>>> defense.com_
>>>> _;!!Dl6pPzL6!fVuNoqxkdCCqescc5hd8-9ke7-
>>> o3uVuZEOBtugdgtfrHUBcO3T2a6LyI_
>>>> lZBwk7CZBJRmOhVQnZHXCdvIB_h5MY$
>>>> 
>>>>> -----Message d'origine-----
>>>>> DeÃ, : Les Chambers <les at chambers.com.au> EnvoyÃf©Ã, : jeudi 22 juin
>>>>> 2023 23:46 Ãfâ,¬Ã, : RICQUE Bertrand (SAFRAN ELECTRONICS & DEFENSE)
>>>>> <bertrand.ricque at safrangroup.com>; koopman.cmu at gmail.com;
>>>>> systemsafety at lists.techfak.uni-bielefeld.de
>>>>> ObjetÃ, : RE: [SystemSafety] AI and the virtuous test Oracle
>>>>> 
>>>>> CAUTION:  This message originated from an outside organization. In
>>>>> case of suspicion, click on "Report to SAFRAN Security" from the 
> Outlook
>>> ribbon.
>>>>> 
>>>>> RE your comment, ââ,¬Å"A neural network is software logic.ââ,¬Â
>>>>> 
>>>>> A neural Network is a component of an AI agent. An AI agent is a
>>>>> suite of general purpose software tools. The agent is configured from a
>>> dataset.
>>>>> 
>>>>> ChatGPT goes on (see dialog below): ââ,¬Å"Synthesizing an AI agent
>>>>> involves training the machine learning model on a large 
> dataset.ââ,¬Â
>>>>> 
>>>>> This indicates that the training dataset determines the agentââ,¬â"¢s
>>>>> behaviour (transfer function - inputs to outputs). In the case of a
>>>>> Tesla motor
>>> vehicle,
>>>>> the inputs are camera sensors and the outputs will soon be controls
>>>>> to the accelerator, brake and steering.
>>>>> 
>>>>> RE your comment, ââ,¬Å"The problem is not AI. It is the exhaustive
>>> deterministic
>>>>> relationship between the undesired losses and the system states.
>>>>> Anything breaking this, breaks the current safety paradigm. And AI
>>>>> is not the single thing to achieve this.ââ,¬Â
>>>>> 
>>>>> Could you please expand on this idea. Possibly using an example.
>>>>> 
>>>>> How would your thought apply here: I am a driver at the wheel of a
>>>>> Tesla travelling at 110 km/h on the freeway. I have switched the
>>>>> vehicle to full
>>> self-
>>>>> driving mode. I am fast asleep. The FSD agent detects a false
>>>>> positive ââ,¬â?o
>>> a lady
>>>>> with a pram. It jams on the brakes initiating a rear-end collision
>>>>> with a following semi.
>>>>> Q: In this case how is it that, ââ,¬Å"The problem is not AIââ,¬Â
>>>>> 
>>>>> Les
>>>>> 
>>>>> ââ,¬â?Ã¢â,¬â?Ã¢â,¬â?Ã¢â,¬â?Ã¢â,¬â? ChatGPT Dialog 
> ââ,¬â?Ã¢â,¬â?Ã¢â,¬â?Ã¢â,¬â?Ã¢â,¬â?Ã¢â,¬â?
>>>>> 
>>>>> ChatGPT prompt:
>>>>> ââ,¬Å"Describe an AI agent from a technical perspective. What are its
>>> components
>>>>> and
>>>>> how is it synthesized?ââ,¬Â
>>>>> 
>>>>> Response:
>>>>> An AI agent, from a technical perspective, typically consists of
>>>>> several components that work together to perform specific tasks.
>>>>> Here are the key components and how they are synthesized:
>>>>> 
>>>>> 1. Data: The foundation of any AI agent is data. It can be in
>>>>> various forms such as text, images, audio, or structured data. This
>>>>> data is used for
>>> training
>>>>> and providing context to the AI model.
>>>>> 
>>>>> 2. Machine Learning Model: The AI agent utilizes a machine learning
>>>>> model
>>> to
>>>>> process and generate responses. These models are trained on vast
>>>>> amounts of data and learn patterns to make predictions or generate
>>>>> outputs.
>>>>> 
>>>>> 3. Natural Language Processing (NLP): NLP is a crucial component for
>>>>> understanding and processing human language. It involves tasks like
>>>>> language translation, sentiment analysis, intent recognition, and
>>>>> entity extraction.
>>> NLP
>>>>> enables the AI agent to comprehend user inputs and generate relevant
>>>>> responses.
>>>>> 
>>>>> 4. Knowledge Representation: Knowledge representation refers to how
>>>>> information is stored and organized within the AI agent. It can
>>>>> employ various
>>> techniques
>>>>> such as semantic networks, ontologies, or graph databases to store
>>>>> facts
>>> and
>>>>> relationships. This allows the agent to access and utilize knowledge
>>>>> when responding to user queries.
>>>>> 
>>>>> 5. Dialogue Management: Dialogue management focuses on handling the
>>>>> flow of conversation. It involves tracking the dialogue context,
>>>>> managing user requests and responses, and generating meaningful and
>>>>> coherent replies.
>>>>> Reinforcement
>>>>> learning techniques can be applied to improve dialogue management.
>>>>> 
>>>>> 6. Integration and APIs: AI agents can integrate with external
>>>>> systems and services using APIs (Application Programming
>>>>> Interfaces). This allows them
>>> to
>>>>> access relevant data sources, databases, or external functionalities
>>>>> to provide more comprehensive and accurate responses.
>>>>> 
>>>>> 7. User Interface: The AI agent needs a user interface to interact
>>>>> with
>>> users
>>>>> effectively. It can be a chat interface, voice-based interface, or a
>>>>> combination of both. The UI should provide a seamless experience for
>>>>> users to interact with the agent.
>>>>> 
>>>>> Synthesizing an AI agent involves training the machine learning
>>>>> model on a large dataset. This process includes steps like
>>>>> preprocessing the data, designing the model architecture, selecting
>>>>> appropriate algorithms,
>>> training
>>>>> the model using optimization techniques, and fine-tuning it for
>>>>> specific
>>> tasks.
>>>>> The trained model is then integrated with other components, such as
>>>>> NLP, knowledge representation, and dialogue management, to create a
>>>>> functioning AI agent. Regular updates, feedback loops, and
>>>>> continuous improvement are essential to enhance the agent's
>>>>> performance over time.
>>>>> 
>>>>> --------END Chat ----------
>>>>> 
>>>>> 
>>>>>> C2 - Confidential
>>>>>> 
>>>>>> The problem is not AI. It is the exhaustive deterministic
>>>>>> relationship
>>>>> between the undesired losses and the system states. Anything
>>>>> breaking this, breaks the current safety paradigm. And AI is not the
>>>>> single thing to
>>> achieve
>>>>> this.
>>>>>> 
>>>>>> AttentionÃfâ?sÃ, : due to increased cybersecurity screening I may
>>>>>> receive
>>>>> external
>>>>> emails 30 minutes after their emission.
>>>>>> RESTRICTED
>>>>>> 
>>>>>> Bertrand RICQUE
>>>>>> Safety and security standardisation Expert Program Support Manager
>>>>>> Optronics and Defence Division/Customer Support Safran Electronics
>>>>>> & Defense
>>>>>> 
>>>>>> P +33 (0)1 58 11 96 82   M +33 (0)6 87 47 84 64
>>>>>> bertrand.ricque at safrangroup.com
>>>>>> 102 Avenue de Paris
>>>>>> 91300 MASSY FRANCE
>>>>>> https://urldefense.com/v3/__http://www.safran-electronics-
>>>>> defense.com__;!!Dl6pPzL6!bg5nEqH6ID136htdDa-
>>>>> 
>>> DgyRz2IZw9arqA9HPKC3p01ZYHoQhzebcyOn5xrgApDNO52A_sLRMk2YgX63j
>>>>> n5fk7M4$
>>>>>> 
>>>>>>> -----Message d'origine-----
>>>>>>> DeÃfâ?sÃ, : systemsafety <systemsafety-bounces at lists.techfak.uni-
>>>>> bielefeld.de>
>>>>>>> De la part de Phil Koopman
>>>>>>> EnvoyÃfÆ'Ã,©Ãfâ?sÃ, : jeudi 22 juin 2023 03:32 
> ÃfÆ'ââ?s¬Ãfâ?sÃ, :
>>>>>>> les at chambers.com.au; systemsafety at lists.techfak.uni-
>>>>> bielefeld.de
>>>>>>> ObjetÃfâ?sÃ, : Re: [SystemSafety] AI and the virtuous test Oracle
>>>>>>> 
>>>>>>> CAUTION:  This message originated from an outside organization.
>>>>>>> In case
>>>>> of
>>>>>>> suspicion, click on "Report to SAFRAN Security" from the Outlook
>>> ribbon.
>>>>>>> 
>>>>>>> Les,
>>>>>>> 
>>>>>>> Since you welcome riffs, I have something that is not as all-
>>> encompassing,
>>>>>>> but might have more immediate application.
>>>>>>> 
>>>>>>> I propose that to the degree that "AI" technology is deployed in
>>>>>>> a way
>>>>> that
>>>>>>> supplants practical human judgement, the manufacturer of that
>>>>>>> system
>>>>> (in
>>>>>>> some cases just the AI part if it is an add-on component) should
>>>>>>> be
>>> held
>>>>>>> accountable for any action (or inaction) that, if associated
>>>>>>> with the
>>> human
>>>>>>> that was supplanted, would have constituted negligence.Ãfâ?sÃ,  
> This
>>>>>>> should
>>>>> include
>>>>>>> situations in which a human is put in an untenable situation of
>>> supervising
>>>>> an
>>>>>>> AI in a way that puts unreasonable demands upon them, amounting
>>>>>>> to a "moral crumple zone"
>>>>>>> approach
>>>>>>> 
>>>>> (https://urldefense.com/v3/__https://papers.ssrn.com/sol3/papers.cfm
>>>>> ?ab
>>>>>>> 
>>>>> 
>>> stract_id=2757236__;!!Dl6pPzL6!dV6V79CEWJVLcdXXS5n2wYWdaCGJCzdLlz4
>>>>>>> gg9Cz063kcikC8CIr0YMf2lF9o5xNrnA0Av-DS0QOuOFaUivQZX7h$ ).
>>>>>>> Liability/negligence if an AI is in substantive control of such
>>>>>>> a
>>> situation
>>>>> should
>>>>>>> attach to the manufacturer.
>>>>>>> 
>>>>>>> This leads to a more narrow oracle, but perhaps still useful,
>>>>>>> than you propose. If a loss event is caused by a lack of
>>>>>>> "reasonable" behavior
>>> by an
>>>>> AI,
>>>>>>> the manufacturer is on the hook for negligence, and the
>>>>>>> AI/manufacturer owes a duty of care the same as the human who
>>>>>>> was supplanted would
>>>>> have
>>>>>>> owed to whoever/whatever might be affected by that negligence.
>>>>>>> It has
>>>>> the
>>>>>>> advantage of reusing existing definitions of "reasonable person"
>>>>>>> that
>>>>> have
>>>>>>> been hammered out over decades of law. (To be sure that is not
>>>>>>> in the
>>>>> form
>>>>>>> of an engineering specification, but case law has a pretty
>>>>>>> robust set
>>> of
>>>>>>> precedents, such as crashing into something after your properly
>>>>> functioning
>>>>>>> vehicle ran a red light is likely to lead to the driver being
>>>>>>> found
>>>>> negligent.)
>>>>>>> 
>>>>>>> This does not require the AI to behave the same as people, and
>>>>>>> is not a
>>>>> full
>>>>>>> recipe for "safe" AI. But it puts a floor on things in a way
>>>>>>> that is
>>>>> readily
>>>>>>> actionable using existing legal mechanisms and theories. If a
>>> reasonable
>>>>>>> person would have avoided a harm, any AI that fails to avoid the
>>>>>>> harm
>>>>> would
>>>>>>> be negligent.
>>>>>>> 
>>>>>>> I've worked with a lawyer to propose this approach for automated
>>>>> vehicles,
>>>>>>> and it is starting to get some traction. What I write in this
>>>>>>> post
>>> (above)
>>>>> is a
>>>>>>> generalization of the concept beyond the narrow automated
>>>>>>> vehicle application.
>>>>>>> Details here:
>>>>>>> 
>>>>> 
>>> https://urldefense.com/v3/__https://safeautonomy.blogspot.com/2023/0
>>>>> 5
>>>>>>> /a-liability-approach-for-
>>>>>>> 
>>>>> 
>>> automated.html__;!!Dl6pPzL6!dV6V79CEWJVLcdXXS5n2wYWdaCGJCzdLlz4gg
>>>>>>> 9Cz063kcikC8CIr0YMf2lF9o5xNrnA0Av-DS0QOuOFaUh295b5I$
>>>>>>> 
>>>>>>> -- Phil
>>>>>>> 
>>>>>>> 
>>>>>>>> On 6/21/2023 7:14 PM, Les Chambers wrote:
>>>>>>>> Hi All
>>>>>>>> 
>>>>>>>> I find myself reflecting on what will become of us.
>>>>>>>> As systems engineering best practice is overrun by AI.
>>>>>>>> 
>>>>>>>> Practitioners report that neural networks are eating code.
>>>>>>>> Example 1: The vector field surrounding a Tesla motor vehicle
>>>>>>>> is an output of a neural network, not the result of software
>>>>>>>> logic. Soon
>>> the
>>>>>>>> neural net - not code - will generate controls. The size of
>>>>>>>> the code base is reducing.  (Elon
>>>>>>>> Musk)
>>>>>>>> Example 2: the ChatGPT transformer code base is only 2000 LOC
>>>>>>>> (Mo Gawdat
>>>>>>>> https://urldefense.com/v3/__https://youtu.be/bk-
>>>>>>> nQ7HF6k4__;!!Dl6pPzL6!
>>>>>>>> 
>>>>>>> 
>>>>> 
>>> dV6V79CEWJVLcdXXS5n2wYWdaCGJCzdLlz4gg9Cz063kcikC8CIr0YMf2lF9o5xN
>>>>>>> rnA0Av
>>>>>>>> -DS0QOuOFaUpIawiVG$ )
>>>>>>>> 
>>>>>>>> The intelligence resides in terabytes of data, perceptrons and
>>>>>>>> millions of weighting parameters. All are gathered by
>>>>>>>> automated
>>>>> means.
>>>>>>>> Not subject to human review.
>>>>>>>> 
>>>>>>>> Ergo what will become of our trusty barriers to dangerous 
> failure:
>>>>>>>> 1. Safety functions - gone
>>>>>>>> 2. Verification - gone
>>>>>>>> 3. Code reviews - gone
>>>>>>>> 4. Validation - How?
>>>>>>>> 
>>>>>>>> On validation, may I suggest the moral AI. A test oracle built
>>>>>>>> on a virtuous dataset, capable of interrogating the target
>>>>>>>> system to determine virtue. Test outcomes will morph from
>>>>>>>> pass/failure to
>>>>>>> moral/immoral.
>>>>>>>> 
>>>>>>>> Credible industry players have predicted that soon we will
>>>>>>>> have AIs orders of magnitude smarter than us. Especially when
>>>>>>>> they start
>>> talking
>>>>> to
>>>>>>> each other.
>>>>>>>> The bandwidth will be eye-watering - the increase in
>>>>>>>> intelligence,
>>>>> vertical.
>>>>>>>> 
>>>>>>>> New barriers are required. Time to develop an AI that is on
>>>>>>>> our side
>>> Ãf¢ââ?s‰â,¬Å"
>>>>>>>> the side of ethics and the moral life. An adult in the room if
>>>>>>>> you like. We should birth this creature now and raise it as good
>>> parents.
>>>>>>>> 
>>>>>>>> Let us not panic. May I put the proposition: virtue, like
>>>>>>>> creativity, can be algorithmic.
>>>>>>>> I have a sense of starting from the beginning - tabula rasa. I
>>> suggest
>>>>>>>> that high-level thinking on the subject could begin with
>>>>>>>> ChatGPT
>>>>> prompts:
>>>>>>>> 1. What is the stoic philosopherÃf¢ââ?s‰â?z¢s concept of 
> virtue?
>>>>>>>> 2. What are the elements of philosophy relevant to AI?
>>>>>>>> 
>>>>>>>> Let us not forget our engineering mission: Guardians of the
>>>>>>>> divine Logos, the organizing principle of the universe,
>>>>>>>> responsible for its creation, maintenance, and order.
>>>>>>>> 
>>>>>>>> Would anyone care to riff on this?
>>>>>>>> 
>>>>>>>> Les
>>>>>>>> 
>>>>>>>> --
>>>>>>>> 
>>>>>>>> Les Chambers
>>>>>>>> 
>>>>>>>> les at chambers.com.au
>>>>>>>> systemsengineeringblog.com
>>>>>>>> 
>>>>>>>> +61 (0)412 648 992
>>>>>>>> _______________________________________________
>>>>>>>> The System Safety Mailing List
>>>>>>>> systemsafety at TechFak.Uni-Bielefeld.DE
>>>>>>>> Manage your subscription:
>>>>>>>> https://urldefense.com/v3/__https://lists.techfak.uni-
>>>>> bielefeld.de/mai
>>>>>>>> 
>>>>>>> 
>>>>> 
>>> lman/listinfo/systemsafety__;!!Dl6pPzL6!dV6V79CEWJVLcdXXS5n2wYWdaC
>>>>>>> GJCz
>>>>>>>> dLlz4gg9Cz063kcikC8CIr0YMf2lF9o5xNrnA0Av-
>>> DS0QOuOFaUjXMdlNF$
>>>>>>>> 
>>>>>>> 
>>>>>>> --
>>>>>>> Prof. Phil Koopman   koopman at cmu.edu
>>>>>>> (he/him)
>>>>>>> 
>>>>> 
>>> https://urldefense.com/v3/__https://users.ece.cmu.edu/*koopman/__;fg!
>>>>>>> 
>>>>> 
>>> !Dl6pPzL6!dV6V79CEWJVLcdXXS5n2wYWdaCGJCzdLlz4gg9Cz063kcikC8CIr0YM
>>>>>>> f2lF9o5xNrnA0Av-DS0QOuOFaUnsUrevc$
>>>>>>> 
>>>>>>> _______________________________________________
>>>>>>> The System Safety Mailing List
>>>>>>> systemsafety at TechFak.Uni-Bielefeld.DE
>>>>>>> Manage your subscription:
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>>>>>>> 
>>>>> 
>>> bielefeld.de/mailman/listinfo/systemsafety__;!!Dl6pPzL6!dV6V79CEWJVL
>>>>> cd
>>>>>>> XXS5n2wYWdaCGJCzdLlz4gg9Cz063kcikC8CIr0YMf2lF9o5xNrnA0Av-
>>>>>>> DS0QOuOFaUjXMdlNF$
>>>>>> 
>>>>>> #
>>>>>> " Ce courriel et les documents qui lui sont joints peuvent
>>>>>> contenir des
>>>>> informations confidentielles, ÃfÆ'Ã,ªtre soumis aux 
> rÃfÆ'Ã,¨glementations
>>> relatives au
>>>>> contrÃfÆ'Ã,´le des exportations ou ayant un caractÃfÆ'Ã,¨re 
> privÃfÆ'Ã,©.
>>>>> S'ils ne
>>> vous sont
>>>>> pas destinÃfÆ'Ã,©s, nous vous signalons qu'il est strictement interdit
>>>>> de les divulguer, de les reproduire ou d'en utiliser de quelque
>>>>> maniÃfÆ'Ã,¨re que ce
>>> soit
>>>>> le contenu. Toute exportation ou rÃfÆ'Ã,©exportation non 
> autorisÃfÆ'Ã,©e
>>>>> est interdite Si ce message vous a ÃfÆ'Ã,©tÃfÆ'Ã,© transmis par 
> erreur,
>>>>> merci d'en informer l'expÃfÆ'Ã,©diteur et de supprimer
>>> immÃfÆ'Ã,©diatement
>>>>> de votre systÃfÆ'Ã,¨me informatique ce courriel ainsi que tous les
>>>>> documents qui y sont attachÃfÆ'Ã,©s."
>>>>>> ******
>>>>>> " This e-mail and any attached documents may contain confidential
>>>>>> or
>>>>> proprietary information and may be subject to export control laws
>>>>> and regulations. If you are not the intended recipient, you are
>>>>> notified that
>>> any
>>>>> dissemination, copying of this e-mail and any attachments thereto or
>>>>> use of their contents by any means whatsoever is strictly
>>>>> prohibited. Unauthorized export or re-export is prohibited. If you
>>>>> have received this e-mail in
>>> error,
>>>>> please advise the sender immediately and delete this e-mail and all
>>> attached
>>>>> documents from your computer system."
>>>>>> #
>>>>> 
>>>>> 
>>>>> 
>>>>> --
>>>>> 
>>>>> Les Chambers
>>>>> 
>>>>> les at chambers.com.au
>>>>> 
>>>>> +61 (0)412 648 992
>>>>> 
>>>> 
>>>> #
>>>> " Ce courriel et les documents qui lui sont joints peuvent contenir
>>>> des
>>> informations confidentielles, Ãfªtre soumis aux rÃf¨glementations 
> relatives au
>>> contrÃf´le des exportations ou ayant un caractÃf¨re privÃf©. S'ils ne 
> vous sont
>>> pas destinÃf©s, nous vous signalons qu'il est strictement interdit de les
>>> divulguer, de les reproduire ou d'en utiliser de quelque maniÃf¨re que ce 
> soit
>>> le contenu. Toute exportation ou rÃf©exportation non autorisÃf©e est
>>> interdite Si ce message vous a Ãf©tÃf© transmis par erreur, merci d'en
>>> informer l'expÃf©diteur et de supprimer immÃf©diatement de votre
>>> systÃf¨me informatique ce courriel ainsi que tous les documents qui y sont
>>> attachÃf©s."
>>>> ******
>>>> " This e-mail and any attached documents may contain confidential or
>>> proprietary information and may be subject to export control laws and
>>> regulations. If you are not the intended recipient, you are notified that 
> any
>>> dissemination, copying of this e-mail and any attachments thereto or use of
>>> their contents by any means whatsoever is strictly prohibited. Unauthorized
>>> export or re-export is prohibited. If you have received this e-mail in 
> error,
>>> please advise the sender immediately and delete this e-mail and all 
> attached
>>> documents from your computer system."
>>>> #
>>> 
>>> 
>>> 
>>> --
>>> 
>>> Les Chambers
>>> 
>>> les at chambers.com.au
>>> 
>>> +61 (0)412 648 992
>>> 
>> 
>> #
>> " Ce courriel et les documents qui lui sont joints peuvent contenir des 
> informations confidentielles, être soumis aux règlementations relatives au 
> contrôle des exportations ou ayant un caractère privé. S'ils ne vous sont 
> pas destinés, nous vous signalons qu'il est strictement interdit de les 
> divulguer, de les reproduire ou d'en utiliser de quelque manière que ce soit 
> le contenu. Toute exportation ou réexportation non autorisée est interdite Si 
> ce message vous a été transmis par erreur, merci d'en informer l'expéditeur 
> et de supprimer immédiatement de votre système informatique ce courriel ainsi 
> que tous les documents qui y sont attachés."
>> ******
>> " This e-mail and any attached documents may contain confidential or 
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>> #
> 
> --
> 
> Les Chambers
> 
> les at chambers.com.au
> 
> +61 (0)412 648 992
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