Futurelyis in the Higher Education Tech Industry

Futurely

Photo by John Schnobrich on Unsplash Gambling is one of the oldest recreational activities in the history of mankind. Its most ancient records date all the way back to the Paleolithic period. The earliest six-sided dice, the one we know today, has been traced back to Mesopotamia some 5,000 years ago! It’s how many Roman soldiers liked to pass their time, wagering their hard-earned coins against each other for fun, and for the chance to end the day with a heavier coin purse. Blockchain casinos are set to be the latest iteration of the online gambling and sports betting industry. Shift back to modern day and we see that . Multiple new game forms have entered the fray and a whole gigantic industry has been built around iconic games like the roulette, poker, sports betting and many others. The Internet helped escalate this to an entire new level with companies being able to offer players the chance to gamble on anything they like from the comfort of their own home. The ubiquitous use of mobile devices further contributed to this growth. gambling has evolved in uncountable ways It is a well documented fact that our DNA has been almost hard-coded to enjoy the thrill of putting our stake on an event whose outcome we don’t know. The variations in levels of neurochemicals such as dopamine are the main drive behind the addictive aspect of gambling. . It comes as no surprise that the entire online gambling market was evaluated at $44 billion in 2016 and is estimated to reach $80 billion by 2022 The global casino market gross gaming yield helps visualize this trend: Retrieved from Statista Keep in mind that none of these numbers take into account all the unthinkable sums of money that are wagered on worldwide. It’s understandably hard to pin down a solid number but vary from to dollars. illegal gambling estimates $80 $380 billion The industry has definitely come a long way and cemented itself into the world of business. However the modern industry practices are from perfect. . From a technological viewpoint the internet is a marvel and it did a wonderful job proliferating industries like this to people all around the globe. However as things stand today it lacks the tools required to overcome the hurdles that plague online casinos and sports books. What are these hurdles? far It has major downfalls that affect the gambling houses, regulators and of course most importantly, the players Lack of transparency and fairness By Masaaki Komori on Unsplash The notable lack of transparency and fairness is something that has afflicted gambling and betting enthusiasts for a long time. . This isn’t always the case, and there is hardly anyway to check if the casino software algorithms are legit or not. If a player is particularly skilled in what he’s doing than he’s even more prone to see his or her winnings cut short by the house. Players have no choice other than to trust the online platforms that they are not being cheated Sports betting platforms are infamous for having everything built around luring the players into losing money, maximizing potential profits in favor of the house. Brick and mortar casinos have notoriously received for cases when members of the security team abruptly approach winning players and put an end to their streak for no particular reason and with no proof of foul play. bad press In online casinos this can be done in a much more silent and subtle way and players won’t even notice. Although most players don’t experience any issues with online gambling houses, there have been numerous cases of complaints regarding payments and bonuses that weren’t properly carried out. Askgamblers alone to have helped over . claims 7,000 players retrieve over $16M in what would be otherwise lost funds Regulation issues High-end regulators often struggle to keep up with the pace of changes to the online gambling industry. And thanks to the bad press around it, the increasing regulatory pressure is not taken slightly by them. Furthermore if the regulations in one country or jurisdiction do not please the company behind online casinos and sportsbooks, it is not unlikely that it will pack up its things and “move” to an offshore regulatory heaven. Securing licenses in places like Curaçao is an industry standard to keep regulatory issues away while also avoiding taxes. This invites users to play in such platforms in hopes of getting better terms, like odds in sports betting events. Often players do this illegally, sometimes without knowledge of the illegality of their actions. The result is not only a tax problem for the country in which those players reside, but also a problem for the players themselves. In a case of rightful complaint they have no legal way to defend themselves. High Entry Barrier To open up account on online platforms players are forced to give up their sensitive personal data like name, address and credit card number. . Deposits and payouts are not instant, and again, lack of transparency, fairness and efficient regulations discourages players from joining. between online gambling houses and potential new players, sapping the industry of the power to reach its full potential. It is far from anonymous This creates friction Blockchain to the rescue? Scott Rodgerson on Unsplash In short, is the revolutionary behind famous cryptocurrencies like and . It is like a decentralized ledger database that operates transparently in a distributed network of computers. It is also capable of running programs that execute under, and only under certain conditions or rules a.k.a s . It’s quite more complex than this, but think of Bitcoin and Ethereum as a fancy programmable form of money, and of blockchain as the database of all the transactions done with these currencies. blockchain Bitcoin Ethereum mart contracts Thanks to this, smart contracts transactions can happen automatically and almost , without the need of going through a third party or central server database. . instantaneously The conditions and rules that apply to these contracts are also enforced automatically by the code that underpins them Whether people like cryptocurrencies or not, the blockchain has come to stay and help improve our lives in ways that we don’t even know yet. It’s compared to the birth of the Internet in the early nineties. What solutions does this bring? If you’ve been in this space for long enough you know how blockchain and its associated cryptocurrencies are changing many of the industries we know today, and even opening doors for new ones and new business models. The relationship between this technology and online gambling however, is one that instantly and vigorously stands out. Remember what the Internet did to mail and messaging back in the day…? So let’s start with the lack of transparency and fairness we mentioned earlier. Blockchain can improve this in more than one way. It can setup the possibility of players to play directly against each other, . Remember, the blockchain is decentralized, there is no need to go through the casino servers in order to wager against a player or a group of players. All payouts can then be carried out by the smart contract protocols we mentioned. It gives the house absolutely no chance to tamper with these payouts, including bonuses and promotions. in a true peer-to-peer system This peer-to-peer gambling creates the chance to bring back the good old days of (technically called ), which the online industry has failed to replicate so far thanks to the lack of technology that would allow it. This is an example of online gambling houses being able to offer players new kinds of services. This concept is already used in some blockchain sportsbooks like . mutual betting Pari-mutuel betting OneHash Provably fair . It means that the casinos can . This is only truly possible through blockchain technology. Since the birth of this concept, the demand for provably fair games has been steadily growing. Gambling houses can offer the players the chance to see the open-source code of the games, or offer other tools for the players to check that they are not being cheated. This is understandably one of the big guns that blockchain casinos have to show for themselves prove that the games they offer are fair and abide by the rules of the game itself Google searches for “Provably fair” over the last 10 years. Viewed on Google Trends This is also beneficial for the casinos because it removes the need for another third party to audit their software. Should the need for a third party verification arise though, the process would be remarkably simpler, which leads us to our next topic. Regulation benefits Regulating blockchain technologies and cryptocurrencies is still a hotly debated topic. However , as well as applicants or licensees. It provides a safe environment for storing and tracking information about transactions, while allowing reliable third-party verification. One could almost be led to think that in the future, regulators would be tempted to require online gambling houses to operate with this technology in order to make their lives easier. many fundamentals aspects this technology may in fact come to the rescue of regulators Take money laundering as an example. The possibility to audit the blockchain in order to review transactions across different operators, and then compare accounts that might be using them to place bets in both sides of events in order to launder dirty money would be a game changer. When it comes to pre-licensing investigations and suitability checks, blockchain-based technology can also help relief concerns regarding standardization and data protection. Lower entry barrier This is very beneficial for online casinos, as we already see happening today. Whether it is just a regular online casino that accepts Bitcoin (or other cryptos) like , or entirely blockchain-based casinos, the process of getting started is much simpler and faster. . The deposit is then quickly processed, sometimes even instantly depending on the cryptocurrency used. In other cases, all you need is the MetaMask browser extension. 1xBit No personal data is required, just an e-mail, a wallet address and a password Being able to bet and gamble without the need of disclosing sensitive data stimulates business. Players can get started within minutes, sometimes even testing out the games for free with whatever amount they can get from the platform’s faucet. Privacy concerned customers who don’t want any gambling bills showing up in credit card statements won’t need to look any further. Security Just this year came out of a casino that had its high-rolling customer database hacked through a thermometer in the lobby fish tank (pretty amazing!). With hackers getting more and more sophisticated, cyber security startups are making a killing as more companies want to be sure that their data is fully secure. Because the blockchain is decentralized, hackers have no central server to attack in order to steal or corrupt data. Bitcoin’s blockchain has been running with 100% uptime and no successful hacks ever since its inception in 2009. news Disruption Potential There is still no way to tell if blockchain technologies will be the future industry norm for online gambling. . However the many intricacies that assemble the blockchain technology will bring new building blocks to this industry Players, regulators and the gambling houses themselves have multiple reasons to welcome it. It is that the online gambling market will reach by 2022. This is the number that blockchain casinos startups will be hoping to tap int. However keep in ming that the global casino market value is much higher at Some casinos have already started to accept cryptocurrency payments, but . In these cases the offer is restricted to deposits and payouts being conducted with Bitcoin or its siblings, which offers some advantages. estimated $80 billion $500 billion. this has nothing to do with being blockchain-based In order to reap all the benefits we mention in this article, a casino would need to run entirely on a blockchain’s decentralized network. Many ICO’s of this kind resort to creating their own token within Ethereum’s chain. Ethereum still operates with some limitations on number of transactions per second, but the resources being poured into improving this are tremendous. FunFair FunFair’s idea is to create games that can only be played using their FUN token (ERC20). What’s impressive about FunFair is how they want to tackle regulation in order to make their product work. They are in talks with many regulators from countries like Malta, which has proclaimed its open policy toward blockchain businesses. They have even for a license in the UK. Other operators would then be able to incorporate their games in their own platforms using FunFair’s license. Like a form of . applied license white labeling Edgeless Edgeless is also an ERC20 token. The difference here is that Edgeless have a fully functional that offers players the ability to play dice and blackjack using their EDG token. They have laid out plans to futurely include poker and sports betting. platform TrueFlip TrueFlip offers their players lottery games that can be played with many cryptocurrencies. Once again you can expect their lottery fairness to be fully auditable, even by yourself. Their ERC20 token TFL offers extra to its holders. rewards Lottery draws happen all the time and in order to participate users have to buy a ticket. They currently offer 4 original games. Conclusion Symbiosis: a mutually beneficial relationship between different people or groups Many new projects are looking to take advantage of blockchain technology to implement it on the online gambling and sports betting business. The advantages are plenty and clear to see. With good implementation the impact on the industry would be huge. Financially speaking, if we judge by market cap only, the biggest of the three we mentioned here is FunFair. Their market cap at the time of writing is $100M. Edgeless sits at $27M. The two combined ($127M) are only a tiny minuscule fraction of the market value of the whole industry. If by estimate the whole blockchain casino industry can grab 10% of the online gambling market, they would sit at a market value of . a conservative $8 billion From a qualitative perspective the cards have all been dealt for blockchain casinos and sports betting platform to lead an inevitable industry improvement. Things are just getting started. Originally published at https://casinosblockchain.io on July 13, 2018.

Blockchain and Online Casinos: Technological Symbiosis

How Useful are Computational Models to Traders in Their Decision Making?

The Future of Work: Preparing for an AI and Machine Learning Dominated Economy

Authors:
(1) Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany (wickert@cs.tu-darmstadt.de);
(2) Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany (baumgaertner@cs.tu-darmstadt.de);
(3) Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany (florian.breitfelder@tu-darmstadt.de);
(4) Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany (mezini@cs.tu-darmstadt.de). Table of Links Abstract and 1 Introduction 2 Background 3 Design and Implementation of Licma and 3.1 Design 3.2 Implementation 4 Methodology and 4.1 Searching and Downloading Python Apps 4.2 Comparison with Previous Studies 5 Evaluation and 5.1 GitHub Python Projects 5.2 MicroPython 6 Comparison with previous studies 7 Threats to Validity 8 Related Work 9 Conclusion, Acknowledgments, and References 9 CONCLUSION In this paper, we presented the first empirical study of crypto misuses in Python. To conduct the study, we implemented the first multi-language analysis tool for crypto misuses with rules to detect common misuses of five different Python libraries as well as the standard Java library. We analyzed 895 popular Python apps from GitHub and 51 MicroPython projects to identify misuses. Our analysis revealed that 52.26 % of the projects using a crypto API, misuse the respective library. Furthermore, we observed that only 7 % of the 1,501 misuses are within the application code. The analysis of embedded applications written in MicroPython revealed the importance of hybrid analysis as the only crypto calls were in C code that got shipped with the projects. To get an impression on the differences between the different domains and languages analyzed in previous studies, we compared our results against the misuses reported for Android apps [4] and C firmware images [13]. Our comparison confirms the impression that an opinionated API design actually helps developers avoiding misuses. While we concentrated on the impact of a user-friendly API design for Python, future work can verify if these results generalize to other languages, like Rust and Go. Thus, extending LICMA with new languages. Further, it may be interesting to extend the currently implemented rules in LICMA by an in-depth analysis of misuses of Python crypto APIs. ACKNOWLEDGMENTS This research work has been co-funded by the Deutsche Forschung gemeinschaft (DFG) – SFB 1119 CROSSING (236615297) and SFB 1053 MAKI (210487104), by the German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE, by the LOEWE initiative (Hesse, Germany) within the emergenCITY center. REFERENCES [1] Yasemin Acar, Michael Backes, Sascha Fahl, Simson Garfinkel, Doowon Kim, Michelle L Mazurek, and Christian Stransky. 2017. Comparing the usability of cryptographic apis. In IEEE Symposium on Security and Privacy (SP). IEEE, 154–171. [2] Yasemin Acar, Christian Stransky, Dominik Wermke, Michelle L Mazurek, and Sascha Fahl. 2017. Security developer studies with github users: Exploring a convenience sample. In Symposium on Usable Privacy and Security (SOUPS). 81– 95. [3] Alexia Chatzikonstantinou, Christoforos Ntantogian, Georgios Karopoulos, and Christos Xenakis. 2016. Evaluation of cryptography usage in android applications. In EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS). 83–90. [4] Manuel Egele, David Brumley, Yanick Fratantonio, and Christopher Kruegel. 2013. An empirical study of cryptographic misuse in android applications. In ACM SIGSAC conference on Computer & communications security (CCS), Ahmad-Reza Sadeghi, Virgil Gligor, and Moti Yung (Eds.). ACM, 73–84. [5] Pietro Ferrara, Amit Kr Mandal, Agostino Cortesi, and Fausto Spoto. 2019. Crossprogramming language taint analysis for the iot ecosystem. Electronic Communications of the EASST 77 (2019). [6] Mohammadreza Hazhirpasand, Mohammad Ghafari, and Oscar Nierstrasz. 2020. Java Cryptography Uses in the Wild. In ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). ACM, Article 40. [7] Christopher Kane, Bo Lin, Saksham Chand, and Yanhong A. Liu. 2018. Highlevel Cryptographic Abstractions. CoRR abs/1810.09065 (2018). arXiv:1810.09065 http://arxiv.org/abs/1810.09065 [8] Stefan Krüger, Johannes Späth, Karim Ali, Eric Bodden, and Mira Mezini. 2018. CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs. In European Conference on Object-Oriented Programming (ECOOP) (Leibniz International Proceedings in Informatics (LIPIcs)), Vol. 109. Schloss Dagstuhl– Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 10:1–10:27. [9] David Lazar, Haogang Chen, Xi Wang, and Nickolai Zeldovich. 2014. Why does cryptographic software fail? A case study and open problems. In Asia-Pacific Workshop on Systems. 1–7. [10] Zaigham Mushtaq, Ghulam Rasool, and Balawal Shehzad. 2017. Multilingual source code analysis: A systematic literature review. IEEE Access 5 (2017), 11307– 11336. [11] Sarah Nadi, Stefan Krüger, Mira Mezini, and Eric Bodden. 2016. Jumping through hoops: Why do Java developers struggle with cryptography APIs?. In International Conference on Software Engineering (ICSE). 935–946. [12] Sazzadur Rahaman, Ya Xiao, Sharmin Afrose, Fahad Shaon, Ke Tian, Miles Frantz, Murat Kantarcioglu, and Danfeng Yao. 2019. Cryptoguard: High precision detection of cryptographic vulnerabilities in massive-sized java projects. In ACM SIGSAC Conference on Computer and Communications Security. 2455–2472. [13] Li Zhang, Jiongyi Chen, Wenrui Diao, Shanqing Guo, Jian Weng, and Kehuan Zhang. 2019. CryptoREX: Large-scale Analysis of Cryptographic Misuse in IoT Devices. In International Symposium on Research in Attacks, Intrusions and Defenses (RAID). USENIX Association, 151–164. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany (wickert@cs.tu-darmstadt.de); (2) Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany (baumgaertner@cs.tu-darmstadt.de); (3) Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany (florian.breitfelder@tu-darmstadt.de); (4) Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany (mezini@cs.tu-darmstadt.de). Authors: Authors: (1) Anna-Katharina Wickert, Technische Universität Darmstadt, Darmstadt, Germany (wickert@cs.tu-darmstadt.de); (2) Lars Baumgärtner, Technische Universität Darmstadt, Darmstadt, Germany (baumgaertner@cs.tu-darmstadt.de); (3) Florian Breitfelder, Technische Universität Darmstadt, Darmstadt, Germany (florian.breitfelder@tu-darmstadt.de); (4) Mira Mezini, Technische Universität Darmstadt, Darmstadt, Germany (mezini@cs.tu-darmstadt.de). Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Background 2 Background 3 Design and Implementation of Licma and 3.1 Design 3 Design and Implementation of Licma and 3.1 Design 3.2 Implementation 3.2 Implementation 4 Methodology and 4.1 Searching and Downloading Python Apps 4 Methodology and 4.1 Searching and Downloading Python Apps 4.2 Comparison with Previous Studies 4.2 Comparison with Previous Studies 5 Evaluation and 5.1 GitHub Python Projects 5 Evaluation and 5.1 GitHub Python Projects 5.2 MicroPython 5.2 MicroPython 6 Comparison with previous studies 6 Comparison with previous studies 7 Threats to Validity 7 Threats to Validity 8 Related Work 8 Related Work 9 Conclusion, Acknowledgments, and References 9 Conclusion, Acknowledgments, and References 9 CONCLUSION In this paper, we presented the first empirical study of crypto misuses in Python. To conduct the study, we implemented the first multi-language analysis tool for crypto misuses with rules to detect common misuses of five different Python libraries as well as the standard Java library. We analyzed 895 popular Python apps from GitHub and 51 MicroPython projects to identify misuses. Our analysis revealed that 52.26 % of the projects using a crypto API, misuse the respective library. Furthermore, we observed that only 7 % of the 1,501 misuses are within the application code. The analysis of embedded applications written in MicroPython revealed the importance of hybrid analysis as the only crypto calls were in C code that got shipped with the projects. To get an impression on the differences between the different domains and languages analyzed in previous studies, we compared our results against the misuses reported for Android apps [4] and C firmware images [13]. Our comparison confirms the impression that an opinionated API design actually helps developers avoiding misuses. While we concentrated on the impact of a user-friendly API design for Python, future work can verify if these results generalize to other languages, like Rust and Go. Thus, extending LICMA with new languages. Further, it may be interesting to extend the currently implemented rules in LICMA by an in-depth analysis of misuses of Python crypto APIs. LICMA ACKNOWLEDGMENTS This research work has been co-funded by the Deutsche Forschung gemeinschaft (DFG) – SFB 1119 CROSSING (236615297) and SFB 1053 MAKI (210487104), by the German Federal Ministry of Education and Research and the Hessen State Ministry for Higher Education, Research and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE, by the LOEWE initiative (Hesse, Germany) within the emergenCITY center. REFERENCES [1] Yasemin Acar, Michael Backes, Sascha Fahl, Simson Garfinkel, Doowon Kim, Michelle L Mazurek, and Christian Stransky. 2017. Comparing the usability of cryptographic apis. In IEEE Symposium on Security and Privacy (SP). IEEE, 154–171. [2] Yasemin Acar, Christian Stransky, Dominik Wermke, Michelle L Mazurek, and Sascha Fahl. 2017. Security developer studies with github users: Exploring a convenience sample. In Symposium on Usable Privacy and Security (SOUPS). 81– 95. [3] Alexia Chatzikonstantinou, Christoforos Ntantogian, Georgios Karopoulos, and Christos Xenakis. 2016. Evaluation of cryptography usage in android applications. In EAI International Conference on Bio-inspired Information and Communications Technologies (formerly BIONETICS). 83–90. [4] Manuel Egele, David Brumley, Yanick Fratantonio, and Christopher Kruegel. 2013. An empirical study of cryptographic misuse in android applications. In ACM SIGSAC conference on Computer & communications security (CCS), Ahmad-Reza Sadeghi, Virgil Gligor, and Moti Yung (Eds.). ACM, 73–84. [5] Pietro Ferrara, Amit Kr Mandal, Agostino Cortesi, and Fausto Spoto. 2019. Crossprogramming language taint analysis for the iot ecosystem. Electronic Communications of the EASST 77 (2019). [6] Mohammadreza Hazhirpasand, Mohammad Ghafari, and Oscar Nierstrasz. 2020. Java Cryptography Uses in the Wild. In ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM). ACM, Article 40. [7] Christopher Kane, Bo Lin, Saksham Chand, and Yanhong A. Liu. 2018. Highlevel Cryptographic Abstractions. CoRR abs/1810.09065 (2018). arXiv:1810.09065 http://arxiv.org/abs/1810.09065 [8] Stefan Krüger, Johannes Späth, Karim Ali, Eric Bodden, and Mira Mezini. 2018. CrySL: An Extensible Approach to Validating the Correct Usage of Cryptographic APIs. In European Conference on Object-Oriented Programming (ECOOP) (Leibniz International Proceedings in Informatics (LIPIcs)), Vol. 109. Schloss Dagstuhl– Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 10:1–10:27. [9] David Lazar, Haogang Chen, Xi Wang, and Nickolai Zeldovich. 2014. Why does cryptographic software fail? A case study and open problems. In Asia-Pacific Workshop on Systems. 1–7. [10] Zaigham Mushtaq, Ghulam Rasool, and Balawal Shehzad. 2017. Multilingual source code analysis: A systematic literature review. IEEE Access 5 (2017), 11307– 11336. [11] Sarah Nadi, Stefan Krüger, Mira Mezini, and Eric Bodden. 2016. Jumping through hoops: Why do Java developers struggle with cryptography APIs?. In International Conference on Software Engineering (ICSE). 935–946. [12] Sazzadur Rahaman, Ya Xiao, Sharmin Afrose, Fahad Shaon, Ke Tian, Miles Frantz, Murat Kantarcioglu, and Danfeng Yao. 2019. Cryptoguard: High precision detection of cryptographic vulnerabilities in massive-sized java projects. In ACM SIGSAC Conference on Computer and Communications Security. 2455–2472. [13] Li Zhang, Jiongyi Chen, Wenrui Diao, Shanqing Guo, Jian Weng, and Kehuan Zhang. 2019. CryptoREX: Large-scale Analysis of Cryptographic Misuse in IoT Devices. In International Symposium on Research in Attacks, Intrusions and Defenses (RAID). USENIX Association, 151–164. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

LICMA's Analysis of Crypto API Misuses in Python Apps: Findings and Future Directions 

This paper is available on arxiv under CC 4.0 license.
Authors:
(1) Kiriaki Frangias;
(2) Andrew Lin;
(3) Ellen Vitercik;
(4) Manolis Zampetakis. Table of Links Abstract and Introduction Warm-up: Agents with known equal disutility Agents with unknown disutilites Experiments Conclusions and future directions, References A Summary of notation B Omitted proofs from Section 2 C Omitted proofs from Section 3 D Additional Information about Experiments 5 Conclusions and future directions We studied the multifaceted problem of designing a crowdsourcing mechanism that efficiently and accurately ranks a set of items using pairwise comparisons from rational agents. We based our approach on the classic principal-agent model from contract theory. To distribute comparisons among agents, we used an unexpected connection to the social golfer problem which allowed us to simultaneously minimize the agents’ workload and ensure enough agents evaluate each comparison. We showed that by optimizing the payment mechanisms, the principal can incentivize enough agents to exert effort, ensuring our algorithm recovers the ground-truth ranking. Our experiments showed that even when noise is added to our original model, our method consistently aids the principal in retrieving the accurate ground-truth ordering. llude, which allowed us to assign the same set of verified comparisons to all agents. How should our mechanism change if agents can collude? Moreover, we assumed that agents who do not exert effort will return comparisons consistent with a uniformly-random permutation of the items. What other models of agent behavior can we study under this framework? Finally, as is standard in contract theory, we assumed that the principal knows the probability π that an effortful agent is good. How should we handle the case where π is unknown? References [1] Abolfazl Asudeh, Gensheng Zhang, Naeemul Hassan, Chengkai Li, and Gergely V. Zaruba. Crowdsourcing pareto-optimal object finding by pairwise comparisons. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (CIKM), 2015. [2] Ralph Allan Bradley and Milton E Terry. Rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39(3/4):324–345, 1952. [3] Yang Cai, Constantinos Daskalakis, and Christos Papadimitriou. Optimum statistical estimation with strategic data sources. In Conference on Learning Theory (COLT), 2015. [4] Xi Chen, Paul N Bennett, Kevyn Collins-Thompson, and Eric Horvitz. Pairwise ranking aggregation in a crowdsourced setting. In Proceedings of the International Conference on Web Search and Data Mining, pages 193–202, 2013. [5] Yuxin Chen and Changho Suh. Spectral MLE: Top-k rank aggregation from pairwise comparisons. In International Conference on Machine Learning (ICML), 2015. [6] Paul Duetting, Tomer Ezra, Michal Feldman, and Thomas Kesselheim. Combinatorial contracts. 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URL https://api.semanticscholar.org/CorpusID:36647621. [16] Jean-Jacques Laffont and David Martimort. Moral Hazard: The Basic Trade-Offs, pages 145–186. Princeton University Press, 2002. URL http://www.jstor.org/stable/j.ctv7h0rwr.8. [17] Shili Lin. Rank aggregation methods. Wiley Interdisciplinary Reviews: Computational Statistics, 2(5):555–570, 2010. [18] Tyler Lu and Craig Boutilier. Learning mallows models with pairwise preferences. In International Conference on Machine Learning (ICML), 2011. [19] C. L. Mallows. Non-null ranking models. i. Biometrika, 44:114–130, 1957. URL https://api.semanticscholar.org/CorpusID:121527283. [20] Fei Mi and Dit-Yan Yeung. Probabilistic graphical models for boosting cardinal and ordinal peer grading in moocs. In AAAI Conference on Artificial Intelligence, 2015. [21] Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong Do, Andrew Ng, and Daphne Koller. Tuned models of peer assessment in moocs. In Proceedings of The 6th International Conference on Educational Data Mining (EDM), 2013. [22] R. L. Plackett. The Analysis of Permutations. Journal of the Royal Statistical Society Series C, 24(2):193–202, June 1975. doi: 10.2307/2346567. URL https://ideas.repec.org/a/bla/jorssc/v24y1975i2p193-202.html. [23] Karthik Raman and Thorsten Joachims. Methods for ordinal peer grading. In International Conference on Knowledge Discovery and Data Mining (KDD), 2014. [24] Karthik Raman and Thorsten Joachims. Bayesian ordinal peer grading. In Proceedings of the ACM Conference on Learning at Scale, 2015. [25] Vikas C Raykar, Shipeng Yu, Linda H Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, and Linda Moy. Learning from crowds. Journal of machine learning research, 11(4), 2010. [26] Nihar Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, and Martin Wainwright. Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2015. [27] Nihar B Shah, Joseph K Bradley, Abhay Parekh, Martin Wainwright, and Kannan Ramchandran. A case for ordinal peer-evaluation in moocs. In NIPS Workshop on Data-Driven Education, 2013. [28] Louis Leon Thurstone. The method of paired comparisons for social values. The Journal of Abnormal and Social Psychology, 21:384–400, 1927. URL https://api.semanticscholar.org/CorpusID:144595330. [29] Markus Triska. Solution Methods for the Social Golfer Problem. PhD thesis, Vienna University of Technology, March 2008. Available from https://www.metalevel.at/mst.pdf. [30] Kristi Tsukida, Maya R Gupta, et al. How to analyze paired comparison data. Department of Electrical Engineering University of Washington, Tech. Rep. UWEETR-2011-0004, 1, 2011. [31] Bo Waggoner and Yiling Chen. Output agreement mechanisms and common knowledge. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1): 220–226, Sep. 2014. doi: 10.1609/hcomp.v2i1.13151. URL https://ojs.aaai.org/index.php/HCOMP/article/view/13151. [32] Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, and Michael I. Jordan. The sample complexity of online contract design. In ACM Conference on Economics and Computation (EC), 2023. This paper is available on Arxiv under CC 4.0 license. This paper is available on arxiv under CC 4.0 license. Authors: (1) Kiriaki Frangias; (2) Andrew Lin; (3) Ellen Vitercik; (4) Manolis Zampetakis. This paper is available on arxiv under CC 4.0 license. Authors : Authors (1) Kiriaki Frangias; (2) Andrew Lin; (3) Ellen Vitercik; (4) Manolis Zampetakis. Table of Links Abstract and Introduction Abstract and Introduction Warm-up: Agents with known equal disutility Warm-up: Agents with known equal disutility Agents with unknown disutilites Agents with unknown disutilites Experiments Experiments Conclusions and future directions, References Conclusions and future directions, References A Summary of notation A Summary of notation B Omitted proofs from Section 2 B Omitted proofs from Section 2 C Omitted proofs from Section 3 C Omitted proofs from Section 3 D Additional Information about Experiments D Additional Information about Experiments 5 Conclusions and future directions We studied the multifaceted problem of designing a crowdsourcing mechanism that efficiently and accurately ranks a set of items using pairwise comparisons from rational agents. We based our approach on the classic principal-agent model from contract theory. To distribute comparisons among agents, we used an unexpected connection to the social golfer problem which allowed us to simultaneously minimize the agents’ workload and ensure enough agents evaluate each comparison. We showed that by optimizing the payment mechanisms, the principal can incentivize enough agents to exert effort, ensuring our algorithm recovers the ground-truth ranking. Our experiments showed that even when noise is added to our original model, our method consistently aids the principal in retrieving the accurate ground-truth ordering. llude, which allowed us to assign the same set of verified comparisons to all agents. How should our mechanism change if agents can collude? Moreover, we assumed that agents who do not exert effort will return comparisons consistent with a uniformly-random permutation of the items. What other models of agent behavior can we study under this framework? Finally, as is standard in contract theory, we assumed that the principal knows the probability π that an effortful agent is good. How should we handle the case where π is unknown? References [1] Abolfazl Asudeh, Gensheng Zhang, Naeemul Hassan, Chengkai Li, and Gergely V. Zaruba. Crowdsourcing pareto-optimal object finding by pairwise comparisons. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (CIKM), 2015. [2] Ralph Allan Bradley and Milton E Terry. Rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39(3/4):324–345, 1952. [3] Yang Cai, Constantinos Daskalakis, and Christos Papadimitriou. Optimum statistical estimation with strategic data sources. In Conference on Learning Theory (COLT), 2015. [4] Xi Chen, Paul N Bennett, Kevyn Collins-Thompson, and Eric Horvitz. Pairwise ranking aggregation in a crowdsourced setting. In Proceedings of the International Conference on Web Search and Data Mining, pages 193–202, 2013. [5] Yuxin Chen and Changho Suh. Spectral MLE: Top-k rank aggregation from pairwise comparisons. In International Conference on Machine Learning (ICML), 2015. [6] Paul Duetting, Tomer Ezra, Michal Feldman, and Thomas Kesselheim. Combinatorial contracts. In Symposium on Foundations of Computer Science (FOCS), 2022. [7] Anindya Ghose, Panagiotis G Ipeirotis, and Beibei Li. Designing ranking systems for hotels on travel search engines by mining user-generated and crowdsourced content. Marketing Science, 31(3):493–520, 2012. [8] John Guiver and Edward Snelson. Bayesian inference for plackett-luce ranking models. In International Conference on Machine Learning (ICML), 2009. [9] Stephen Guo, Aditya Parameswaran, and Hector Garcia-Molina. So who won? dynamic max discovery with the crowd. In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD ’12, page 385–396, New York, NY, USA, 2012. Association for Computing Machinery. ISBN 9781450312479. doi: 10.1145/2213836.2213880. URL https://doi.org/10.1145/2213836.2213880. [10] Guru Guruganesh, Jon Schneider, and Joshua Wang. Contracts under moral hazard and adverse selection. In ACM Conference on Economics and Computation (EC), 2021. [11] R. Jurca and B. Faltings. Mechanisms for making crowds truthful. Journal of Artificial Intelligence Research, 34:209–253, mar 2009. doi: 10.1613/jair.2621. URL https://doi.org/10.1613%2Fjair.2621. [12] Radu Jurca and Boi Faltings. Robust incentive-compatible feedback payments. In Workshop on Trading Agent Design and Analysis, 2006. [13] Radu Jurca and Boi Faltings. Minimum payments that reward honest reputation feedback. In ACM Conference on Economics and Computation (EC), 2006. [14] Jiawen Kang, Zehui Xiong, Dusit Niyato, Dongdong Ye, Dong In Kim, and Jun Zhao. Toward secure blockchain-enabled internet of vehicles: Optimizing consensus management using reputation and contract theory. IEEE Transactions on Vehicular Technology, 68(3):2906–2920, 2019. [15] Ngai Meng Kou, Yan Li, Hao Wang, Leong Hou U, and Zhiguo Gong. Crowdsourced top-k queries by confidence-aware pairwise judgments. Proceedings of the 2017 ACM International Conference on Management of Data, 2017. URL https://api.semanticscholar.org/CorpusID:36647621. [16] Jean-Jacques Laffont and David Martimort. Moral Hazard: The Basic Trade-Offs, pages 145–186. Princeton University Press, 2002. URL http://www.jstor.org/stable/j.ctv7h0rwr.8. [17] Shili Lin. Rank aggregation methods. Wiley Interdisciplinary Reviews: Computational Statistics, 2(5):555–570, 2010. [18] Tyler Lu and Craig Boutilier. Learning mallows models with pairwise preferences. In International Conference on Machine Learning (ICML), 2011. [19] C. L. Mallows. Non-null ranking models. i. Biometrika, 44:114–130, 1957. URL https://api.semanticscholar.org/CorpusID:121527283. [20] Fei Mi and Dit-Yan Yeung. Probabilistic graphical models for boosting cardinal and ordinal peer grading in moocs. In AAAI Conference on Artificial Intelligence, 2015. [21] Chris Piech, Jonathan Huang, Zhenghao Chen, Chuong Do, Andrew Ng, and Daphne Koller. Tuned models of peer assessment in moocs. In Proceedings of The 6th International Conference on Educational Data Mining (EDM), 2013. [22] R. L. Plackett. The Analysis of Permutations. Journal of the Royal Statistical Society Series C, 24(2):193–202, June 1975. doi: 10.2307/2346567. URL https://ideas.repec.org/a/bla/jorssc/v24y1975i2p193-202.html. [23] Karthik Raman and Thorsten Joachims. Methods for ordinal peer grading. In International Conference on Knowledge Discovery and Data Mining (KDD), 2014. [24] Karthik Raman and Thorsten Joachims. Bayesian ordinal peer grading. In Proceedings of the ACM Conference on Learning at Scale, 2015. [25] Vikas C Raykar, Shipeng Yu, Linda H Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, and Linda Moy. Learning from crowds. Journal of machine learning research, 11(4), 2010. [26] Nihar Shah, Sivaraman Balakrishnan, Joseph Bradley, Abhay Parekh, Kannan Ramchandran, and Martin Wainwright. Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence. In International Conference on Artificial Intelligence and Statistics (AISTATS), 2015. [27] Nihar B Shah, Joseph K Bradley, Abhay Parekh, Martin Wainwright, and Kannan Ramchandran. A case for ordinal peer-evaluation in moocs. In NIPS Workshop on Data-Driven Education, 2013. [28] Louis Leon Thurstone. The method of paired comparisons for social values. The Journal of Abnormal and Social Psychology, 21:384–400, 1927. URL https://api.semanticscholar.org/CorpusID:144595330. [29] Markus Triska. Solution Methods for the Social Golfer Problem. PhD thesis, Vienna University of Technology, March 2008. Available from https://www.metalevel.at/mst.pdf. [30] Kristi Tsukida, Maya R Gupta, et al. How to analyze paired comparison data. Department of Electrical Engineering University of Washington, Tech. Rep. UWEETR-2011-0004, 1, 2011. [31] Bo Waggoner and Yiling Chen. Output agreement mechanisms and common knowledge. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2(1): 220–226, Sep. 2014. doi: 10.1609/hcomp.v2i1.13151. URL https://ojs.aaai.org/index.php/HCOMP/article/view/13151. [32] Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, and Michael I. Jordan. The sample complexity of online contract design. In ACM Conference on Economics and Computation (EC), 2023. This paper is available on Arxiv under CC 4.0 license. This paper is available on Arxiv under CC 4.0 license. Arxiv

Algorithmic Contract Design for Crowdsourced Ranking: Conclusions, Future Directions, and References

Authors: (1) Renato P. dos Santos, CIAGE – Centre for Generative Artificial Intelligence in Cognition and Education. Table of Links Abstract and Introduction Materials And Methods Results and Analyses Prompts and generated texts Conceptualizing chemical reactions Deepening on understanding of chemical reactions Question about combustion Question about a graph of gases turning into water over time Question about the difference between atoms, molecules, and moles Deepening on the concept of mole Question about changing of state Question about an animated representation of water molecules undergoing phase changes Question about plasma, a state of matter Question about chemical bondings Question about illustration of chemical bonds Question about the essence of the type of chemical bonding Further analysis Conclusions Limitations of the study and possible future studies Author Contributions, Conflicts of interest, Acknowledgements, and References Limitations of the study and possible future studies Despite its inherent limitations, including its single case design and the potential for bias, the exploratory depth of the study uncovered hidden potential within these systems, even amid serious concerns about generalizability. Future research could include: • Refining the crafting of prompts. • Exploring new features of these and other GenAIbots being introduced with increasing frequency. • Establishing standardised benchmarks to evaluate and compare chatbots and AI systems' performance, accuracy, and reliability. • Conducting long-term studies to observe the evolution of chatbots' capabilities and their impact on user interactions over time. • Conducting research with real students in classroom settings and beyond to assess these AI systems' practical educational applications and challenges. • Investigating chatbots' learning and adaptation capabilities to individual user needs and preferences over time. • Researching the integration of multimodal inputs (e.g., text, voice, image) to enhance chatbot capabilities and user interaction experiences. When implementing GenAIbots in Chemistry learning, it is crucial to evaluate benefits and drawbacks judiciously, ensuring accurate information delivery and considering the implications of reduced human interaction. These concerns may be alleviated by integrating GenAIbots with other educational tools or activities promoting collaborative dialogue among learners. Author Contributions The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation. Conflicts of interest There are no conflicts to declare. Acknowledgements The authors warmly acknowledge Melanie Swan for her invaluable suggestion, which led to the transition from using the term 'objects-to-think-with' to 'agents-to-thinkwith'. References Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionising education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152 Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4337484 Bardin, L. (1977). L’analyse de contenu. PUF - Presses Universitaires de France. Bitzenbauer, P. (2023). ChatGPT in physics education: A pilot study on easy-to-implement activities. Contemporary Educational Technology, 15(3), ep430. https://doi.org/10.30935/cedtech/13176 Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners. ArXiv, 2005.14165. http://arxiv.org/abs/2005.14165 Castro Nascimento, C. M., & Pimentel, A. S. (2023). Do Large Language Models Understand Chemistry? A Conversation with ChatGPT. Journal of Chemical Information and Modeling, 63(6), 1649–1655. https://doi.org/10.1021/acs.jcim.3c00285 David, E. (2023, September 21). Microsoft to add DALL-E 3 to Bing Chat. The Verge; Vox Media. https://www.theverge.com/2023/9/21/23873690/microsoft-new-ai-features-bingsearch-shopping-dall-e-3 Dewi, C. A., Pahriah, P., & Purmadi, A. (2021). The Urgency of Digital Literacy for Generation Z Students in Chemistry Learning. International Journal of Emerging Technologies in Learning, 16(11), 88–103. https://doi.org/10.3991/ijet.v16i11.19871 Dunlop, L., Hodgson, A., & Stubbs, J. E. (2020). Building capabilities in chemistry education: happiness and discomfort through philosophical dialogue in chemistry. Chemistry Education Research and Practice, 21(1), 438–451. https://doi.org/10.1039/C9RP00141G Flavell, J. H. (1976). Metacognitive aspects of problem-solving. In L. B. Resnick (Ed.), The Nature of Intelligence (pp. 231–236). Lawrence Erlbaum. Floridi, L., & Chiriatti, M. (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1 Franciscu, S. (2023). ChatGPT: A Natural Language Generation Model for Chatbots. https://doi.org/10.13140/RG.2.2.24777.83044 Gregorcic, B., & Pendrill, A.-M. (2023). ChatGPT and the frustrated Socrates. Physics Education, 58(3), 035021. https://doi.org/10.1088/1361-6552/acc299 Latour, B. (1991). Nous n’avons jamais été modernes: Essai d’anthropologie symétrique. La Découverte. Leon, A. J., & Vidhani, D. (2023). ChatGPT Needs a Chemistry Tutor, Too. Journal of Chemical Education. https://doi.org/10.1021/acs.jchemed.3c00288 Liu, F., Budiu, R., Zhang, A., & Cionca, E. (2023, October 1). ChatGPT, Bard, or Bing Chat? Differences Among 3 Generative-AI Bots. https://www.nngroup.com/articles/ai-botcomparison/ Metz, C., & Hsu, T. (2023, September 20). ChatGPT Can Now Generate Images, Too. New York Times - Technology. https://www.nytimes.com/2023/09/20/technology/chatgpt-dalle3-images-openai.html Mishra, A., Soni, U., Arunkumar, A., Huang, J., Kwon, B. C., & Bryan, C. (2023). PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models. ArXiv, 2304.01964. https://doi.org/10.48550/arXiv.2304.01964 Mollick, E. R. (2023, April 26). A guide to prompting AI (for what it is worth): A little bit of magic,but mostly just practice. One Useful Thing Blog. https://www.oneusefulthing.org/p/a-guidetoprompting-ai-for-what Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033 OpenAI. (2023). GPT-4 Technical Report. OpenAI. https://cdn.openai.com/papers/gpt-4.pdf Papert, S. A. (1980). Mindstorms - Children, Computers and Powerful Ideas. Basic Books. http://www.arvindguptatoys.com/arvindgupta/mindstorms.pdf Permatasari, M. B., Rahayu, S., & Dasna, W. (2022). Chemistry Learning Using Multiple Representations: A Systematic Literature Review. J.Sci.Learn.2022, 5(2), 334–341. https://doi.org/10.17509/jsl.v5i2.42656 Pimentel, A., Wagener, A., Silveira, E. F. da, Picciani, P., Salles, B., Follmer, C., & Jr., O. N. O. (2023). Challenging ChatGPT with Chemistry-Related Subjects. ChemRxiv. https://doi.org/10.26434/chemrxiv-2023-xl6w3 Schlosser, M. (2019). Agency. In The Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/archives/win2019/entries/agency/ Swan, M. (2015, January 21). We Should Consider the Future World as one of Multi-Species Intelligence. Response to The Edge Question 2015: What Do You Think About Machines That Think?; Edge.org. http://edge.org/response-detail/26070 Taylor, C. A., Hogarth, H., Hacking, E. B., & Bastos, E. (2022). Posthuman Object Pedagogies: Thinking with Things to Think with Theory for Innovative Educational Research. Cultural and Pedagogical Inquiry, 14(1), 206–221. https://doi.org/10.18733/cpi29662 Timilsena, N. P., Maharjan, K. B., & Devkota, K. M. (2022). Teachers’ And Students’ Experiences In Chemistry Learning Difficulties. Journal of Positive School Psychology, 6(10), 2856–2867. https://www.journalppw.com/index.php/jpsp/article/view/13764 Tümay, H. (2016). Reconsidering learning difficulties and misconceptions in chemistry: emergence in chemistry and its implications for chemical education. Chemistry Education Research and Practice, 17(2), 229–245. https://doi.org/10.1039/C6RP00008H Turkle, S. (1984). The Second Self: Computers and the Human Spirit. Simon and Schuster. Yin, R. K. (2011). Applications of Case Study Research. SAGE Publications, Inc. This paper is under CC BY-SA 4.0 DEED license. available on arxiv

Overcoming Limitations in AI Chatbot Research for Future Educational Impact

ভবিষ্যতের শিক্ষাগত প্রভাবের জন্য এআই চ্যাটবট গবেষণায় সীমাবদ্ধতা অতিক্রম করা

Überwindung von Einschränkungen in der KI-Chatbot-Forschung für zukünftige Bildungseffekte

Superar las limitaciones en la investigación de chatbots de IA para lograr un impacto educativo futuro

Surmonter les limites de la recherche sur les chatbots IA pour un impact éducatif futur

भविष्य के शैक्षिक प्रभाव के लिए AI चैटबॉट अनुसंधान में सीमाओं पर काबू पाना

将来の教育への影響のために AI チャットボット研究の限界を克服する

미래 교육적 영향을 위한 AI 챗봇 연구의 한계 극복

Superando as limitações na pesquisa do AI Chatbot para um impacto educacional futuro

Преодоление ограничений в исследованиях чат-ботов с использованием искусственного интеллекта для будущего воздействия на образование

Gelecekteki Eğitim Etkisi için Yapay Zeka Chatbot Araştırmalarında Sınırlamaların Aşılması

Khắc phục những hạn chế trong nghiên cứu Chatbot AI để tạo ra tác động giáo dục trong tương lai

克服人工智能聊天机器人研究的局限性，为未来教育带来影响

The Growing Impact of Electric Vehicles in India's Sustainable Future

Delivering renewable energy solutions that are both efficient and environmentally conscious requires a deep understanding of engineering, project management, and global market dynamics. Leading professionals in this sector are tasked with not only advancing technology but also addressing the logistical and regulatory challenges of diverse terrains and markets worldwide. In this edition of the "Power Leader" series, we explore these themes with Ken Kozicki, Chief Marketing Officer, FTC Solar. Our discussion covers the intricacies of solar tracker systems, key engineering breakthroughs, and strategic decisions that have shaped the industry. This feature offers a nuanced perspective on how top companies are navigating the complex landscape of renewable energy, emphasizing both their successes and the challenges they face. FTC Solar has made significant strides in this direction, delivering over 4.5 GW of solar trackers globally and executing projects across varied landscapes from the United States to Southeast Asia and Australia. The company's deep-rooted experience in engineering and project development has positioned it as a key player in the renewable energy sector. What is FTC Solar's mission and how are your solar tracker systems influencing the renewable energy landscape? At FTC Solar, our mission is deeply rooted in enhancing the competitiveness and sustainability of solar technology. With over two decades of collective experience from our founding team in EPCs (engineering, procurement and construction), developers and asset owners, we've identified and addressed critical industry challenges. Our solutions—spanning differentiated solar trackers, sophisticated software, and comprehensive engineering services—are designed to minimize capital and operational expenses while optimizing energy output. Our global projects, from the United States to Southeast Asia, not only demonstrate our commitment to spreading clean energy but also highlight our role in reducing carbon footprints and aiding communities in their sustainable energy transitions. Can you delve into some of the key engineering innovations about the Voyager+? The Voyager+ stands out as a premier 2P tracker, especially suited for challenging terrains and diverse soil conditions. Its design prioritizes construction efficiency and rapid installation, setting industry benchmarks with significant cost savings on materials. The Voyager+’s engineering success stems from its ability to offer unparalleled design flexibility and operational reliability, leading to a superior return on investment for our clients. Key innovations include our Slide & Guide module installation mechanism, which simplifies the mounting process akin to hanging a picture. Moreover, the tracker reduces the need for piles by 46%, cuts labor costs, and decreases DC wiring by 35%, enhancing overall project efficiency. https://vimeo.com/572125375?embedable=true Under your leadership, FTC Solar has seen rapid expansion globally. What do you attribute this success to, and how do you maintain competitive edge in such a fast-evolving market? Our rapid global expansion can be attributed to two fundamental elements: our core values and our diverse international team. At FTC Solar, we uphold values of customer centricity, integrity, innovation, accountability, and excellence—principles that permeate every aspect of our operations and project delivery. Additionally, our global presence, with teams stationed across nine international locations, equips us with a unique perspective on the solar industry’s diverse challenges and opportunities. This broad outlook, free from regional biases, enables us to effectively tailor our strategies and solutions to meet varied market demands. FTC Solar places a strong emphasis on customer collaboration. Can you provide examples of how this approach has shaped product development and project execution at FTC Solar? Customer centricity is at the heart of everything we do at FTC Solar. Our product development process is deeply collaborative, rooted in a thorough understanding of our customers’ current and future challenges. By engaging closely with our clients, we gather valuable insights that inform our innovations and operational strategies. For instance, our hands-on approach includes joint on-site assembly of the first solar array row and comprehensive training programs, ensuring that every project adheres to best practices while fostering a smooth installation process. This proactive engagement not only enhances project outcomes but also strengthens our customer relationships, driving our collective success. What are some of the biggest challenges FTC Solar has faced in scaling up operations internationally, and how have you adapted your strategy to overcome them? One significant challenge in international markets has been advocating for the adoption of solar trackers over traditional fixed-tilt systems. We've addressed this through extensive customer education on the long-term value and reliability of our tracking solutions. Another major hurdle has been adapting our supply chain to align with local regulations and content requirements. For example, in markets like South Africa, we've expanded our supplier base to include local businesses, thereby not only complying with local mandates but also fostering community growth and development. How do you see FTC evolving to meet future workplace safety and productivity needs? At FTC Solar, safety is paramount—no aspect of our operations supersedes the health and well-being of our team. We are committed to continuous improvement of our safety protocols and procedures, ensuring that our work environment adheres to the highest standards of safety and health. Looking forward, we aim to integrate advanced safety technologies and refine our operational protocols to further enhance workplace safety and productivity. What are the next big trends or technologies in solar energy that you think will significantly impact the industry, and how is FTC Solar preparing to be at the forefront of these changes? Staying ahead of industry trends is crucial, and at FTC Solar, we pride ourselves on our forward-thinking approach. FTC’s zero-stow strategy has been core to our innovation driving lower costs for our customers, and which also, technically, reduces structural stress during high-wind events and prevents modules from microcracking damage. We are also focusing on designs that expedite installation and reduce costs, which is increasingly important due to rising labor shortages and costs. As a leader in the renewable energy sector, how does FTC Solar integrate sustainability and corporate responsibility into its business practices and product development? Sustainability is integral to our operations at FTC Solar. We adhere to strict environmental management systems aligned with ISO 14001 standards, aiming for continuous improvement in our sustainability practices. Our commitment extends beyond compliance to proactive environmental stewardship, which involves setting and achieving stringent environmental targets, conducting regular audits, and engaging our entire workforce in our sustainability initiatives. By fostering an environment of responsibility and awareness, we ensure that our business practices not only meet but exceed the expectations of our stakeholders and contribute positively. Delivering renewable energy solutions that are both efficient and environmentally conscious requires a deep understanding of engineering, project management, and global market dynamics. Leading professionals in this sector are tasked with not only advancing technology but also addressing the logistical and regulatory challenges of diverse terrains and markets worldwide. In this edition of the "Power Leader" series, we explore these themes with Ken Kozicki, Chief Marketing Officer, FTC Solar . Our discussion covers the intricacies of solar tracker systems, key engineering breakthroughs, and strategic decisions that have shaped the industry. This feature offers a nuanced perspective on how top companies are navigating the complex landscape of renewable energy, emphasizing both their successes and the challenges they face. FTC Solar FTC Solar has made significant strides in this direction, delivering over 4.5 GW of solar trackers globally and executing projects across varied landscapes from the United States to Southeast Asia and Australia. The company's deep-rooted experience in engineering and project development has positioned it as a key player in the renewable energy sector. What is FTC Solar's mission and how are your solar tracker systems influencing the renewable energy landscape? What is FTC Solar's mission and how are your solar tracker systems influencing the renewable energy landscape? At FTC Solar, our mission is deeply rooted in enhancing the competitiveness and sustainability of solar technology. With over two decades of collective experience from our founding team in EPCs (engineering, procurement and construction), developers and asset owners, we've identified and addressed critical industry challenges. Our solutions—spanning differentiated solar trackers, sophisticated software, and comprehensive engineering services—are designed to minimize capital and operational expenses while optimizing energy output. Our global projects, from the United States to Southeast Asia, not only demonstrate our commitment to spreading clean energy but also highlight our role in reducing carbon footprints and aiding communities in their sustainable energy transitions. Can you delve into some of the key engineering innovations about the Voyager+? Can you delve into some of the key engineering innovations about the Voyager+? The Voyager+ stands out as a premier 2P tracker, especially suited for challenging terrains and diverse soil conditions. Its design prioritizes construction efficiency and rapid installation, setting industry benchmarks with significant cost savings on materials. The Voyager+’s engineering success stems from its ability to offer unparalleled design flexibility and operational reliability, leading to a superior return on investment for our clients. Key innovations include our Slide & Guide module installation mechanism, which simplifies the mounting process akin to hanging a picture. Moreover, the tracker reduces the need for piles by 46%, cuts labor costs, and decreases DC wiring by 35%, enhancing overall project efficiency. https://vimeo.com/572125375?embedable=true https://vimeo.com/572125375?embedable=true Under your leadership, FTC Solar has seen rapid expansion globally. What do you attribute this success to, and how do you maintain competitive edge in such a fast-evolving market? Under your leadership, FTC Solar has seen rapid expansion globally. What do you attribute this success to, and how do you maintain competitive edge in such a fast-evolving market? Our rapid global expansion can be attributed to two fundamental elements: our core values and our diverse international team. At FTC Solar, we uphold values of customer centricity, integrity, innovation, accountability, and excellence—principles that permeate every aspect of our operations and project delivery. Additionally, our global presence, with teams stationed across nine international locations, equips us with a unique perspective on the solar industry’s diverse challenges and opportunities. This broad outlook, free from regional biases, enables us to effectively tailor our strategies and solutions to meet varied market demands. FTC Solar places a strong emphasis on customer collaboration. Can you provide examples of how this approach has shaped product development and project execution at FTC Solar? FTC Solar places a strong emphasis on customer collaboration. Can you provide examples of how this approach has shaped product development and project execution at FTC Solar? Customer centricity is at the heart of everything we do at FTC Solar. Our product development process is deeply collaborative, rooted in a thorough understanding of our customers’ current and future challenges. By engaging closely with our clients, we gather valuable insights that inform our innovations and operational strategies. For instance, our hands-on approach includes joint on-site assembly of the first solar array row and comprehensive training programs, ensuring that every project adheres to best practices while fostering a smooth installation process. This proactive engagement not only enhances project outcomes but also strengthens our customer relationships, driving our collective success. What are some of the biggest challenges FTC Solar has faced in scaling up operations internationally, and how have you adapted your strategy to overcome them? What are some of the biggest challenges FTC Solar has faced in scaling up operations internationally, and how have you adapted your strategy to overcome them? One significant challenge in international markets has been advocating for the adoption of solar trackers over traditional fixed-tilt systems. We've addressed this through extensive customer education on the long-term value and reliability of our tracking solutions. Another major hurdle has been adapting our supply chain to align with local regulations and content requirements. For example, in markets like South Africa, we've expanded our supplier base to include local businesses, thereby not only complying with local mandates but also fostering community growth and development. How do you see FTC evolving to meet future workplace safety and productivity needs? How do you see FTC evolving to meet future workplace safety and productivity needs? At FTC Solar, safety is paramount—no aspect of our operations supersedes the health and well-being of our team. We are committed to continuous improvement of our safety protocols and procedures, ensuring that our work environment adheres to the highest standards of safety and health. Looking forward, we aim to integrate advanced safety technologies and refine our operational protocols to further enhance workplace safety and productivity. What are the next big trends or technologies in solar energy that you think will significantly impact the industry, and how is FTC Solar preparing to be at the forefront of these changes? What are the next big trends or technologies in solar energy that you think will significantly impact the industry, and how is FTC Solar preparing to be at the forefront of these changes? Staying ahead of industry trends is crucial, and at FTC Solar, we pride ourselves on our forward-thinking approach. FTC’s zero-stow strategy has been core to our innovation driving lower costs for our customers, and which also, technically, reduces structural stress during high-wind events and prevents modules from microcracking damage. We are also focusing on designs that expedite installation and reduce costs, which is increasingly important due to rising labor shortages and costs. As a leader in the renewable energy sector, how does FTC Solar integrate sustainability and corporate responsibility into its business practices and product development? As a leader in the renewable energy sector, how does FTC Solar integrate sustainability and corporate responsibility into its business practices and product development? Sustainability is integral to our operations at FTC Solar. We adhere to strict environmental management systems aligned with ISO 14001 standards, aiming for continuous improvement in our sustainability practices. Our commitment extends beyond compliance to proactive environmental stewardship, which involves setting and achieving stringent environmental targets, conducting regular audits, and engaging our entire workforce in our sustainability initiatives. By fostering an environment of responsibility and awareness, we ensure that our business practices not only meet but exceed the expectations of our stakeholders and contribute positively.

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