In 2018 we witnessed a clash of titans as government and tech companies collided on privacy issues around collecting, culling and using personal data. From GDPR to Facebook scandals, many tech CEOs were defending big data, its use, and how they’re safeguarding the public.
1. Companies will face increased pressure about the data AI-embedded services use.
2. Public concern will lead to AI regulations. But we must understand this tech too.
In 2018, the National Science Foundation invested $100 million in AI research, with special support in 2019 for developing principles for safe, robust and trustworthy AI; addressing issues of bias, fairness and transparency of algorithmic intelligence; developing deeper understanding of human-AI interaction and user education; and developing insights about the influences of AI on people and society.
This investment was dwarfed by DARPA—an agency of the Department of Defence—and its multi-year investment of more than $2 billion in new and existing programs under the “AI Next” campaign. A key area of the campaign includes pioneering the next generation of AI algorithms and applications, such as “explainability” and common sense reasoning.
“Formulating a product, you better know about ethics and understand legal frameworks.”
These days a growing number of people are concerned with bringing more talk of ethics into technology. One question is whether that will bring change to data-science curricula.
Following major data breaches and privacy scandals at tech companies like Facebook, universities including Stanford, the University of Texas and Harvard have all added ethics courses into computer science degree programs to address tech’s “ethical dark side,” the New York Times has reported.
As more college and universities consider incorporating humanities courses into technical degree programs, some are asking what kind of ethics should be taught.
Between the “dumb” fixed algorithms and true AI lies the problematic halfway house we’ve already entered with scarcely a thought and almost no debate, much less agreement as to aims, ethics, safety, best practice. If the algorithms around us are not yet intelligent, meaning able to independently say “that calculation/course of action doesn’t look right: I’ll do it again”, they are nonetheless starting to learn from their environments. And once an algorithm is learning, we no longer know to any degree of certainty what its rules and parameters are. At which point we can’t be certain of how it will interact with other algorithms, the physical world, or us. Where the “dumb” fixed algorithms – complex, opaque and inured to real time monitoring as they can be – are in principle predictable and interrogable, these ones are not. After a time in the wild, we no longer know what they are: they have the potential to become erratic. We might be tempted to call these “frankenalgos” – though Mary Shelley couldn’t have made this up.
Twenty years ago, George Dyson anticipated much of what is happening today in his classic book Darwin Among the Machines. The problem, he tells me, is that we’re building systems that are beyond our intellectual means to control. We believe that if a system is deterministic (acting according to fixed rules, this being the definition of an algorithm) it is predictable – and that what is predictable can be controlled. Both assumptions turn out to be wrong.“It’s proceeding on its own, in little bits and pieces,” he says. “What I was obsessed with 20 years ago that has completely taken over the world today are multicellular, metazoan digital organisms, the same way we see in biology, where you have all these pieces of code running on people’s iPhones, and collectively it acts like one multicellular organism.“There’s this old law called Ashby’s law that says a control system has to be as complex as the system it’s controlling, and we’re running into that at full speed now, with this huge push to build self-driving cars where the software has to have a complete model of everything, and almost by definition we’re not going to understand it. Because any model that we understand is gonna do the thing like run into a fire truck ’cause we forgot to put in the fire truck.”
Walsh believes this makes it more, not less, important that the public learn about programming, because the more alienated we become from it, the more it seems like magic beyond our ability to affect. When shown the definition of “algorithm” given earlier in this piece, he found it incomplete, commenting: “I would suggest the problem is that algorithm now means any large, complex decision making software system and the larger environment in which it is embedded, which makes them even more unpredictable.” A chilling thought indeed. Accordingly, he believes ethics to be the new frontier in tech, foreseeing “a golden age for philosophy” – a view with which Eugene Spafford of Purdue University, a cybersecurity expert, concurs. Where there are choices to be made, that’s where ethics comes in.
our existing system of tort law, which requires proof of intention or negligence, will need to be rethought. A dog is not held legally responsible for biting you; its owner might be, but only if the dog’s action is thought foreseeable.
As we wait for a technological answer to the problem of soaring algorithmic entanglement, there are precautions we can take. Paul Wilmott, a British expert in quantitative analysis and vocal critic of high frequency trading on the stock market, wryly suggests “learning to shoot, make jam and knit”
The venerable Association for Computing Machinery has updated its code of ethics along the lines of medicine’s Hippocratic oath, to instruct computing professionals to do no harm and consider the wider impacts of their work.
Künstliche Intelligenzen und Roboter werden in unserem Leben immer selbstverständlicher. Was erwarten wir von den intelligenten Maschinen, wie verändert ihre Präsenz in unserem Alltag und die Interaktion mit ihnen unser Selbstverständnis und unseren Umgang mit anderen Menschen? Müssen wir Roboter als eine Art menschliches Gegenüber anerkennen? Und welche Freiheiten wollen wir den Maschinen einräumen? Es ist dringend an der Zeit, die ethischen und rechtlichen Fragen zu klären.
1954 wurdeUnimate, der erste Industrieroboter , von George Devol entwickelt . Insbesondere in den 1970er Jahren haben viele produzierende Gewerbe eine Roboterisierung ihrer Arbeit erfahren (beispielsweise die Automobil- und Druckindustrie).
Definition eines Industrieroboters in der ISO 8373 (2012) vergegenwärtigt: »Ein Roboter ist ein frei und wieder programmierbarer, multifunktionaler Manipulator mit mindestens drei unabhängigen Achsen, um Materialien, Teile, Werkzeuge oder spezielle Geräte auf programmierten, variablen Bahnen zu bewegen zur Erfüllung der verschiedensten Aufgaben«.
Ethische Überlegungen zu Robotik und Künstlicher Intelligenz
Versucht man sich einen Überblick über die verschiedenen ethischen Probleme zu verschaffen, die mit dem Aufkommen von ›intelligenten‹ und in jeder Hinsicht (Präzision, Geschwindigkeit, Kraft, Kombinatorik und Vernetzung) immer mächtigeren Robotern verbunden sind, so ist es hilfreich, diese Probleme danach zu unterscheiden, ob sie
1. das Vorfeld der Ethik,
2. das bisherige Selbstverständnis menschlicher Subjekte (Anthropologie) oder
3. normative Fragen im Sinne von: »Was sollen wir tun?« betreffen.
Die folgenden Überlegungen geben einen kurzen Aufriss, mit welchen Fragen wir uns jeweils beschäftigen sollten, wie die verschiedenen Fragenkreise zusammenhängen, und woran wir uns in unseren Antworten orientieren können.
Aufgabe der Ethik ist es, solche moralischen Meinungen auf ihre Begründung und Geltung hin zu befragen und so zu einem geschärften ethischen Urteil zu kommen, das idealiter vor der Allgemeinheit moralischer Subjekte verantwortet werden kann und in seiner Umsetzung ein »gelungenes Leben mit und für die Anderen, in gerechten Institutionen«  ermöglicht. Das ist eine erste vage Richtungsangabe.
Normative Fragen lassen sich am Ende nur ganz konkret anhand einer bestimmten Situation bearbeiten. Entsprechend liefert die Ethik hier keine pauschalen Urteile wie: »Roboter sind gut/schlecht«, »Künstliche Intelligenz dient dem guten Leben/ist dem guten Leben abträglich«.
Etiquette is the proper way to behave and Ethics studies ideas about good and bad behavior. Both combine into Professionalism, which is the skill, good judgment, and polite behavior expected from a person trained to do a job such as social media marketing. Because social media blurs the lines between our personal and professional lives it is useful to look at actions in social media from three perspectives: Personal (as an individual), Professional (as an employee or perspective employee) and Brand (as an organization). To simplify the discussion I have created questions for each category in the Social Media Etiquette and Ethics Guide below. Click here to download.
Before you post or comment in a personal capacity consider:
Is it all about me? No one likes someone who only talks about themselves. The same applies in social media. Balance boasting with complimenting.
Am I stalking someone? It is good to be driven and persistent but be careful not to cross the line into creepy. Don’t be too aggressive in outreach.
Am I spamming them? Not everything or even the majority of what you post should ask for something. Don’t make everything self-serving.
Am I venting or ranting? Venting and ranting may feel good, but research says it doesn’t help and no matter how justified you feel, it never presents you in a positive light. Do not post negative comments or gossip.
Did I ask before I tagged? You had a great time and want to share those memories, but your friends, family or employer may have different standards than a friends. Check before you tag people in posts.
Did I read before commenting or sharing? Don’t make yourself look foolish by not fully reviewing something you are commenting on or sharing with others. Don’t jump to conclusions.
Am I grateful and respectful? Don’t take people for granted. Respond and thank those who engage with you.
Is this the right medium for the message? Not everything should be said in social media. Consider the feelings of the other person. Some messages should be given in person, by phone or email.
Am I logged into the right account? There are too many corporate examples of embarrassing posts meant for personal jokes that went out on official brand accounts. Always double check which account you are on. Don’t post personal information on brand accounts.
Before you post or comment as a professional consider:
Does it meet the Social Media Policy? Most organizations have official social media policies that you probably received when hired. Don’t assume you know what the policy says. Many employees have been fired for not following company social media regulations. Make sure you know and follow employer or client requirements.
Does it hurt my company’s reputation? No matter how many disclaimers you put on your accounts such as “views are my own” certain content and behavior will negatively impact your employer. If your bio states where you work, your personal account represents your employer.
Does it help my company’s marketing? Employee advocacy is an important strategy. Have a positive impact on your company’s image and when you can advocate for your brand in social.
Would my boss/client be happy to see it? You may not have “friended” your boss or client but a co-worker may have and your post is only a share or screen grab away. Even private accounts are never fully private.
Am I being open about who I work for? It is good to post positive content about your employer and it is nice to receive gifts, but if you are trying to pass it off as unbiased opinion that is wrong. Be transparent about your financial connections.
Am I being fair and accurate? Everyone is entitled to their person opinion, but if your opinion tends to always be unfounded and seems to have an agenda it will reflect negatively upon you. Criticism is welcome when it is constructive and opinion is backed by evidence.
Am I being respectful and not malicious? People can get very insensitive, judgmental and angry in social media posts. That does not convey a professional image. Don’t post what you wouldn’t say in person. Even an outburst in person fades in memory, but a malicious post is there forever.
Does it respect intellectual property? Not everything on the Internet is free. Check for or get permission to post company or client brand assets and content.
Is this confidential information? As an employee or contractor you are granted access to privileged and confidential information. Don’t assume it is fine to share. Do not disclose non-public company or client information.
Before posting or commenting as a brand on a social account consider:
Does it speak to my target market? Social media is unique from traditional marketing and requires a different perspective to be effective. Be sure to focus on your target’s wants and needs not yours.
Does it add value? Social media only works if people view and share it. Make your content educational, insightful or entertaining to grab interest and draw engagement.
Does it fit the social channel? Don’t post content ideal for Twitter on Instagram or Reddit. Each channel has its own culture and community. Make sure each post fits the channel’s environment, mission and policies or standards.
Is it authentic and transparent? Trying to trick people into clicking a link or making a purchase will get you nowhere. Don’t hide or exclude any relevant information.
Is it real and unique? Bots can automate tasks and be a great time saver, but use them for the right actions. Don’t use auto responses and create anything that could be perceived as spam.
Is it positive and respectful? It may be fine to talk trash about competitors or complain about customers in the office, but not in social media. Don’t badmouth the competition or customers.
Does it meet codes of conduct? As professionals we are part of trade associations that set standards of conduct. Be sure you are meeting these ethical standards such as the Word of Mouth Marketing Association’s Code of Ethics.
Does it meet all laws and regulations? Government has been catching up with social media and have issued regulations and laws you must follow. See guides on requirements like the FTC social media endorsement guidelines.
Does it meet the Social Media Policy? Most likely your brand or a client’s brand has a social media policy. Ensure you follow your own company standards.
Whether the NYC police angle is true or not (it’s being hotly disputed), Facebook and Google are thinking along lines that follow the whims of the Chinese Government.
SenseTime and Megvii won’t just be worth $5 Billion, they will be worth many times that in the future. This is because a facial recognition data-harvesting of everything is the future of consumerism and capitalism, and in some places, the central tenet of social order (think Asia).
China has already ‘won’ the trade-war, because its winning the race to innovation. America doesn’t regulate Amazon, Microsoft, Google or Facebook properly, that stunts innovation and ethics in technology where the West is now forced to copy China just to keep up.
Session 2: The Digital Age: The Impact and Future Possibilities Offered by Data and Technology
Thank you for registering to participate in the second Reimagining Minnesota State forum. The Forums have been designed to spark not only individual reflection but what we hope can serve as catalysts for discussions in a variety of venues. The Forum will be recorded and available for viewing on the Reimagining website.
Below are the directions whether you are attending in person or by live stream.
Catherine Haslag: Is there any research to show students retention in an online class vs a face-to-face course?
the challenge is not collecting, but integrating, using data.
silos = cylinder of excellence.
technology innovation around advising. iPASS resources.
adaptive learning systems – how students advance through the learning process.
games and simulations Bryan Mark Gill. voice recognition,
next 3 to 5 years AR. by 2023 40% with AR and VR
AI around the controversial. Chatbot and Voice assistants.
Unizin: 13 founding members to develop platform, Canvas, instructional services, data for predictive analytic, consistent data standard among institutions,
University innovation Alliance. Analytics as the linchpin for students’ success. graduation rates increase. racial gap graduation. Georgia State.
digital ethics. Mark Gill and Susana Nuccetelli. digital ethics: Susana Nuccetelli brought her students from the Philosophy Dept to Mark Gill’s SCSu Vizlab so we can discuss ethics and AI, last semester. email@example.com
assistant vice president for student success and prevention Morgan State U
the importance of training in technology adoption
Dr. Peter Smith, Orkand Endowed Chair and Professor of Innovative Practices in Higher Education at University of Maryland University College
social disruption, national security issue,
Allan Taft Candadian researcher, 700 hours / year learning something. 14 h/w.
learners deserve recognition
free range learning.
how do we get a value on people from a different background? knowledge discrimination. we value it on where they learned it. then how you learned it and what you can do with it. talent and capacity not recognized.
we, the campus, don’t control the forces for a very first time. MIT undergrad curricula is free, what will happen. dynamics at work here. declining student numbers, legislation unhappy. technology had made college more expensive, not less. doing the right thing, leads to more disruption. local will be better, if done well. workplace can become a place for learning.
learning is a social activity. distance learning: being on the farthest raw of 300 Princeton lecture. there is a tool and there is people; has to have people at the heart.
what will work not only for MN, but for each of the campuses, the personalization.
staying still is death.
what is the role of faculty in the vendor and discussions about technology. a heat map shows that IT people were testing the vendor web site most, faculty and student much less.