Franziska Günzel

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Franziska Günzel

Franziska Günzel

@FranziskaGunzel

I ❤️ #entrepreneurship, the processes of market and firm emergence, organizational models for social change. Associate Prof @AarhusBSS.

Arhus, Denmark Katılım Nisan 2012
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Franziska Günzel
Franziska Günzel@FranziskaGunzel·
So happy this is out! Our recent @jbv_insights study shows how #entrepreneurs contribute with social innovations to mitigating the #COVID19 crisis through improvised venturing, rapid pivots and pro-social market extensions. authors.elsevier.com/c/1cNKZ8MxvtVL… @MGMTBSS @itim_bss #SDGs
Ali Gümüsay @guemuesay.bsky.social@Guemuesay

Happy to share a new co-authored open access publication on digital social innovation sciencedirect.com/science/articl… #covid19 #crisis #digitalization #entrepreneurship #socialinnovation

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Valerio Capraro
Valerio Capraro@ValerioCapraro·
How effective is human-AI collaboration? A meta-analysis of 106 studies just published in @NaturHumBehav reports an interesting result: On average, there was no synergy: Human–AI combinations did not perform better than both humans and AI. In particular, when the AI alone outperformed the human alone, the human–AI combination led to performance losses, likely because humans were unable to integrate the suggestions provided by the AI. Conversely, when the human outperformed the AI alone, there was some synergy and human–AI combination led to performance gains, likely because this time humans were better at integrating the AI suggestions. Paper: nature.com/articles/s4156…
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Ethan Mollick
Ethan Mollick@emollick·
For parents who want to help their kids with a hard school concept but don't want them to use AI directly: Show the LLM the problem your kid is stuck on and prompt: "how can I, as a parent, explain to my kid, grade N, how to solve this" and then use the advice to help tutor them
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Christian Busch
Christian Busch@ChrisSerendip·
Are you looking for effective ways to develop your ideas into a top management journal article? Check out this insightful new editorial in the Academy of Management Journal (@AOMConnect) by Sinziana Dorobantu, @MarcBGruber, Davide Ravasi, and Ned Wellman. They introduce the "AMJ Management Research Canvas," a valuable tool for mapping out your paper ideas. You can read it here: journals.aom.org/doi/full/10.54….
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Ella Hafermalz
Ella Hafermalz@ellahafermalz·
If you did a masters thesis with a qualitative orientation and are interested in studying AI@Work please consider applying to join us at the VU! werkenbij.vu.nl/vacatures/two-…
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Lorenzo Skade
Lorenzo Skade@LorenzoSkade·
How do AI work professionals deal with the moral issues associated with potential harms that may come with creative ideas? 🤔 "Bright & dark imagining: How creators navigate moral consequences of developing ideas for artificial intelligence" 💡(👉🏾 journals.aom.org/doi/epub/10.54…)
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Matt Beane
Matt Beane@mattbeane·
Right. Yet: Most = 75% of companies saw no change in need for workers, given genAI use. 10% saw decreased need. 15% saw need for different kinds (i.e., replacing 15%). 2% saw increased need. If accurate, these are big employment changes, really fast, actually.
James Pethokoukis ⏩️⤴️@JimPethokoukis

Most companies using AI report it has not affected their need for workers. A financial services firm noted, “AI is helpful in offloading workload and increasing productivity, but we are not at the point where AI is going to replace workers.” dallasfed.org/research/econo…

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Matt Beane
Matt Beane@mattbeane·
This is it, folks, this is it! The "GPTs are GPTs" paper is now officially published in @ScienceMagazine. Massive kudos to the authors for the impressive revisions, and I'm so glad you got (I presume) such thoughtful reviewers. Really excited to dig in. Everyone must read.
Daniel Rock@danielrock

Really excited to see our paper w/@manlikemishap @thankyourniceAi @sj_manning out today in @sciencemagazine. Link here: science.org/doi/10.1126/sc… tl;dr: Studying where LLMs might affect workers, we find that GPTs are GPTs! But what does that mean and how did we do it? 🧵

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Adam Grant
Adam Grant@AdamMGrant·
Hey managers: to keep your people, let them work from home 2 days a week. Landmark experiment (1600+ ppl, 2yrs): random assignment to hybrid work -Increased satisfaction -Reduced quitting by 33% (especially for women & long commuters) -No costs for performance or promotion rates
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Matt Beane
Matt Beane@mattbeane·
The Skill Code: How to Save Human Ability in an Age of Intelligent Machines is off to the printer! Nearly four years ago, I began the messy, ill-advised journey of writing it, and early praise says it delivers. Pre-order, learn more: theskillcodebook.com #TheSkillCode 🧬
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Matt Beane
Matt Beane@mattbeane·
Join in! Tomorrow, 9am pst I present new research @erikbryn's @DigEconLab on how workers and automation can complement each other. “Engineering Skill: How Developing AI-Enabled Robots and Nonprofessional Ability Went Hand in Hand at JointBot” Register: tinyurl.com/34z3khkz
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Luiza Jarovsky, PhD
Luiza Jarovsky, PhD@LuizaJarovsky·
🚨 AI Policy Alert: The German Federal Office for Information Security publishes the report "Generative AI Models - Opportunities and Risks for Industry and Authorities." Quotes & comments: "LLMs are trained based on huge text corpora. The origin of these texts and their quality are generally not fully verified due to the large amount of data. Therefore, personal or copyrighted data, as well as texts with questionable, false, or discriminatory content (e.g., disinformation, propaganda, or hate messages), may be included in the training set. When generating outputs, these contents may appear in these outputs either verbatim or slightly altered (Weidinger, et al., 2022). Imbalances in the training data can also lead to biases in the model" (page 9) - "If individual data points are disproportionately present in the training data, there is a risk that the model cannot adequately learn the desired data distribution and, depending on the extent, tends to produce repetitive, one-sided, or incoherent outputs (known as model collapse). It is expected that this problem will increasingly occur in the future, as LLM-generated data becomes more available on the internet and is used to train new LLMs (Shumailov, et al., 2023). This could lead to self-reinforcing effects, which is particularly critical in cases where texts with abuse potential have been generated, or when a bias in text data becomes entrenched. This happens, for example, as more and more relevant texts are produced and used again for training new models, which in turn generate a multitude of texts (Bender, et al., 2021)." (page 10) - "The high linguistic quality of the model outputs, combined with user-friendly access via APIs and the enormous flexibility of responses from currently popular LLMs, makes it easier for criminals to misuse the models for a targeted generation of misinformation (De Angelis, et al., 2023), propaganda texts, hate messages, product reviews, or posts for social media." ➡️ According to the report, special attention should be given to the following aspects: ➵ Raising awareness of users; ➵ Testing; ➵ Handling sensitive data; ➵ Establishing transparency; ➵ Auditing of inputs and outputs; ➵ Paying attention to (indirect) prompt injections; ➵ Selection and management of training data; ➵ Developing practical expertise. ➡️ Of the dozens of AI reports published lately, this one is especially detailed regarding AI-related risk and potential countermeasures. ➡️The document is a must-read for people developing AI or working on AI policymaking and regulation, especially pages 8-28. ➡️ Link to the @BSI_Bund report below. ➡️ For more information on AI policy and regulation, subscribe to my weekly newsletter (link in bio).
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James Wright
James Wright@jms_wright·
UNESCO’s Ethics of AI team is recruiting! We're looking for 6 experts to contribute to cutting-edge projects on the ethical governance of AI across the following workstreams (please note the deadlines for applications are 16-17 April):
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I-X
I-X@ImperialX_AI·
"Nurturing a space where women can grow authentically can offer a whole new perspective to the #AI world." To celebrate Women at Imperial Week, we spoke to our I-X experts about the impact of #AI on #genderequality.💙 Hear from #OurImperial community ⬇️ imperial.ac.uk/news/251845/br…
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Daron Acemoglu
Daron Acemoglu@DAcemogluMIT·
What will AI do? In most cases, the answer is: AI will do whatever we choose it to do. The direction of new technology is not predetermined, it is a choice that is up to us. Thank you again to all who joined the launch of @MITshapingwork, there is much more to come.
MIT Stone Center on Inequality & Shaping Work@MITshapingwork

In this clip from his opening remarks at our launch event, @DAcemogluMIT urges us not to ask passively what #AI will do to jobs, but instead ask ourselves: How should our society and institutions shape the direction of AI? Watch the full remarks: youtube.com/watch?v=Tmbdyn…

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Ethan Mollick
Ethan Mollick@emollick·
🚨 Our new paper: we know that GPT-4 generates better ideas than most people, but the ideas are kind of similar & variance matters But it turns out that better prompting can generate pools of good ideas that are almost as diverse as from a group of humans papers.ssrn.com/sol3/papers.cf…
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Hans Berends
Hans Berends@hansberendsVU·
Are you interested in applying Process Research Methods in your PhD research? In March 2024 I am offering a course at KIN / Vrije Universiteit Amsterdam, including a three-day module on campus and online sessions. More information & enrollment: vu.nl/en/education/p…
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