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For a long time, there were things on this planet that only humans could do, but this time might be coming to an end. By using the universal tool that makes us unique – our intelligence – we have worked to eliminate our uniqueness, at least when it comes to solving cognitive tasks. Artificial intelligence is now able to play chess, understand language, and drive a car – and often better than we.
How did we get here? The philosopher Aristotle formulated the first “laws of thought” in his syllogisms, and the mathematicians Blaise Pascal and Wilhelm Leibniz built some of the earliest calculating machines. The mathematician George Boole was the first to introduce a formal language to represent logic. The natural scientist Alan Turing created his deciphering machine “Colossus,” the first programmable computer. Philosophers, mathematicians, psychologists, and linguists – for centuries, scientists have been developing formulas, machines, and theories that were supposed to enable us to reproduce and possibly even enhance our most valuable ability.
But what exactly is “artificial intelligence”? Even the name calls for comparison. Is artificial intelligence like human intelligence? Alan Turing came up with a test in 1950 to provide a satisfying operational definition of intelligence: According to him, a machine is intelligent if its thinking abilities equal those of humans. It has to reach human levels for any cognitive task. The machine has to prove this by convincing a human interrogator that it is human. Not an easy task: After all, it has to process natural language, store knowledge, draw conclusions, and learn something new. In fact, over the past ten years, a number of AI systems have emerged that have passed the test one way or another in chat conversations with automatically generated texts or images. Nowadays, the discussion usually centers on other questions: Does AI still need its creators? Will it not only outperform humans but someday replace them – be it in the world of work or even beyond? Will AI solve our problems in the age of all-encompassing digital networking – or will it become a part of the problem?
Artificial intelligence, its nature, its limitations, its potential, and its relationship to humans were being discussed even before it existed. Literature and film have created scenarios with very different endings. But what is the view of the scientists who are actually researching with or about artificial intelligence? For the current issue of our research magazine, a cognitive scientist, an education researcher, and a computer scientist shared their views. We also searched the University for projects whose professional environment reveals the numerous opportunities that AI offers for various disciplines. We cover the geosciences and computer science as well as economics, health, and literature studies.
At the same time, we have not lost sight of the broad research spectrum at the University: a legal expert introduces us to the not-so-distant sphere of space law while astrophysicists work on ensuring that state-of-the-art telescopes observe those regions in space where something “is happening” at the right time. A chemist explains why the battery of the future will come from a printer, and molecular biologists explain how they will breed stress-resistant plants. You will read about all this in this issue as well as about current studies on restless legs syndrome in children and the situation of Muslims in Brandenburg. Last but not least, we will introduce you to the sheep currently grazing in Sanssouci Park – all on behalf of science. Quite clever!
Enjoy your read!
THE EDITORS
Lange gab es auf der Erde Dinge, die konnte nur der Mensch. Doch diese Zeit könnte zu Ende gehen. Mithilfe des universalen Werkzeugs, das uns einzigartig macht – unserer Intelligenz –, haben wir dafür gesorgt, dass wir es nicht länger sind. Zumindest wenn es darum geht, kognitive Aufgaben zu lösen. Künstliche Intelligenz kann inzwischen Schach spielen, Sprache verstehen, Auto fahren. Vieles sogar besser als wir. Wie kam es dazu?
Der Philosoph Aristoteles schuf mit seinen Syllogismen die ersten „Gesetze des Denkens“, die Mathematiker Blaise Pascal und Wilhelm Leibniz bauten einige der frühesten Rechenmaschinen, der Mathematiker George Boole führte als erster eine formale Sprache zur Darstellung der Logik ein, der Naturwissenschaftler Alan Turing schuf mit seiner Dechiffriermaschine „Colossus“ den ersten programmierbaren Computer. Philosophen, Mathematiker, Psychologen, Linguisten – seit Jahrhunderten entwickeln Wissenschaftlerin- nen und Wissenschaftler Formeln, Maschinen und Theorien, die es möglich machen sollen, unsere wertvollste Fähigkeit zu reproduzieren und womöglich sogar zu verbessern. Aber was ist das eigentlich: „Künstliche Intelligenz“?
Schon die Bezeichnung fordert zum Vergleich auf. Ist Künstliche Intelligenz wie menschliche Intelligenz? Alan Turing formulierte 1950 einen Test, der eine befriedigende operationale Definition von Intelligenz liefern sollte: Intelligent ist eine Maschine demnach, wenn sie ein dem Menschen gleichwertiges Denkvermögen besitzt. Sie muss also bei beliebigen kognitiven Aufgaben dasselbe Niveau erreichen. Beweisen muss sie dies, indem sie einen menschlichen Fragenden glauben lässt, sie sei ein Mensch. Keine leichte Sache: Immerhin muss sie dafür natürliche Sprache verarbeiten, Wissen speichern, aus diesem Schlüsse ziehen und Neues lernen können. Tatsächlich entstanden in den vergangenen zehn Jahren etliche KI-Systeme, die in Chat- Gesprächen, mit automatisch erzeugten Texten oder Bildern den Test auf die eine oder andere Weise bestanden. Im Fokus stehen nun meist andere Fragen: Braucht KI ihre Schöpfer überhaupt noch? Wird sie den Menschen nicht nur überflügeln, sondern eines Tages sogar ersetzen – sei es in der Welt der Arbeit oder sogar darüber hinaus? Löst KI im Zeitalter der allumfassenden digitalen Vernetzung unsere Probleme – oder wird sie Teil davon?
Über Künstliche Intelligenz, ihr Wesen, ihre Beschränkungen, ihr Potenzial und ihr Verhältnis zum Menschen wird nicht erst diskutiert seitdem es sie gibt. Vor allem Literatur und Kino haben Szenarien mit verschiedenstem Ausgang kreiert. Aber wie sehen das Wissenschaftler, die mit oder zu Künstlicher Intelligenz forschen? Für die aktuelle Ausgabe des Forschungsmagazins kamen ein Kognitionswissenschaftler, eine Bildungsforscherin und ein Informatiker darüber ins Gespräch. Daneben haben wir uns in der Hochschule nach Projekten umgesehen, deren fachliche Heimat die zahlreichen Möglichkeiten offenbart, die KI für viele Disziplinen erahnen lässt. So geht die Reise in die Geowissenschaften und die Informatik ebenso wie die Wirtschafts-, Gesundheits- und Literaturwissenschaften.
Daneben haben wir die Breite der Forschung an der Universität nicht aus den Augen verloren: Ein Jurist führt ein in die gar nicht so weltferne Sphäre des Weltraumrechts, während Astrophysiker daran arbeiten, dass modernste Teleskope zum richtigen Zeitpunkt genau in die Regionen des Weltraums schauen, wo gerade etwas „los ist“. Eine Chemikerin erklärt, warum die Batterie der Zukunft aus dem Drucker kommt, und Molekularbiologen berichten, wie sie stressresistente Pflanzen züchten wollen. Mit menschlichem Stress in der Arbeitswelt beschäftigt sich nicht nur ein Forschungs-, sondern auch ein Gründerprojekt. Darüber ist in diesem Heft genauso zu lesen wie über aktuelle Studien zum Restless Legs Syndrom bei Kindern oder aber der Situation von Muslimen in Brandenburg. Nicht zuletzt machen wir Sie mit jenen Schafen bekannt, die derzeit im Park Sanssouci weiden – im Auftrag der Wissenschaft. Gar nicht so dumm! Viel Vergnügen!
Die Redaktion
Larix populations at the tundra-taiga ecotone in northern Siberia are highly under-represented in population genetic studies, possibly due to the remoteness of these regions that can only be accessed at extraordinary expense. The genetic signatures of populations in these boundary regions are therefore largely unknown. We aim to generate organelle reference genomes for the detection of single nucleotide polymorphisms (SNPs) that can be used for paleogenetic studies. We present 19 complete chloroplast genomes and mitochondrial genomic sequences of larches from the southern lowlands of the Taymyr Peninsula (northernmost range of Larix gmelinii (Rupr.) Kuzen.), the lower Omoloy River, and the lower Kolyma River (both in the range of Larix cajanderi Mayr). The genomic data reveal 84 chloroplast SNPs and 213 putatively mitochondrial SNPs. Parsimony-based chloroplast haplotype networks show no spatial structure of individuals from different geographic origins, while the mitochondrial haplotype network shows at least a slight spatial structure with haplotypes from the Omoloy and Kolyma populations being more closely related to each other than to most of the haplotypes from the Taymyr populations. Whole genome alignments with publicly available complete chloroplast genomes of different Larix species show that among official plant barcodes only the rcbL gene contains sufficient polymorphisms, but has to be sequenced completely to distinguish the different provenances. We provide 8 novel mitochondrial SNPs that are putatively diagnostic for the separation of L. gmelinii and L. cajanderi, while 4 chloroplast SNPs have the potential to distinguish the L. gmelinii/ L. cajanderi group from other Larix species. Our organelle references can be used for a targeted primer and probe design allowing the generation of short amplicons. This is particularly important with regard to future investigations of, for example, the biogeographic history of Larix by screening ancient sedimentary DNA of Larix.
Das Werk analysiert umfassend das Verbrechen der Aggression im Sinne des Römischen Statuts. Ausgehend von der Rechtsgeschichte, werde die einschlägigen Artikel 8bis, 15bis und 15ter des Römischen Statuts, also die Definition des Verbrechens der Aggression, analysiert.
Ebenso behandelt das Buch weiterführende Entwicklungen des Verbrechens der Aggression über das Jahr 2017 hinaus – das Jahr, in dem es, wahrscheinlich, zu einer Entscheidung über die Aktivierung der Gerichtsbarkeit kommt
Anti-Consumption
(2019)
Transcending the conventional debate around efficiency in sustainable consumption, anti-consumption patterns leading to decreased levels of material consumption have been gaining importance. Change agents are crucial for the promotion of such patterns, so there may be lessons for governance interventions that can be learnt from the every-day experiences of those who actively implement and promote sustainability in the field of anti-consumption. Eighteen social innovation pioneers, who engage in and diffuse practices of voluntary simplicity and collaborative consumption as sustainable options of anti-consumption share their knowledge and personal insights in expert interviews for this research. Our qualitative content analysis reveals drivers, barriers, and governance strategies to strengthen anti-consumption patterns, which are negotiated between the market, the state, and civil society. Recommendations derived from the interviews concern entrepreneurship, municipal infrastructures in support of local grassroots projects, regulative policy measures, more positive communication to strengthen the visibility of initiatives and emphasize individual benefits, establishing a sense of community, anti-consumer activism, and education. We argue for complementary action between top-down strategies, bottom-up initiatives, corporate activities, and consumer behavior. The results are valuable to researchers, activists, marketers, and policymakers who seek to enhance their understanding of materially reduced consumption patterns based on the real-life experiences of active pioneers in the field.
Transcending the conventional debate around efficiency in sustainable consumption, anti-consumption patterns leading to decreased levels of material consumption have been gaining importance. Change agents are crucial for the promotion of such patterns, so there may be lessons for governance interventions that can be learnt from the every-day experiences of those who actively implement and promote sustainability in the field of anti-consumption. Eighteen social innovation pioneers, who engage in and diffuse practices of voluntary simplicity and collaborative consumption as sustainable options of anti-consumption share their knowledge and personal insights in expert interviews for this research. Our qualitative content analysis reveals drivers, barriers, and governance strategies to strengthen anti-consumption patterns, which are negotiated between the market, the state, and civil society. Recommendations derived from the interviews concern entrepreneurship, municipal infrastructures in support of local grassroots projects, regulative policy measures, more positive communication to strengthen the visibility of initiatives and emphasize individual benefits, establishing a sense of community, anti-consumer activism, and education. We argue for complementary action between top-down strategies, bottom-up initiatives, corporate activities, and consumer behavior. The results are valuable to researchers, activists, marketers, and policymakers who seek to enhance their understanding of materially reduced consumption patterns based on the real-life experiences of active pioneers in the field.