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p:ki:fische_nachlese [2024/05/02 08:57] Tscherter Vincentp:ki:fische_nachlese [2025/08/27 11:34] (aktuell) – [2. Verfahren konstruieren] Tscherter Vincent
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 {{ gem/pageinfo}}{{gem/mgr}} {{ gem/pageinfo}}{{gem/mgr}}
 ====== 🐟 Rückschau: Künstliche Intelligenz für echte Fische ====== ====== 🐟 Rückschau: Künstliche Intelligenz für echte Fische ======
-[{{ :p:pasted:fish0191.jpg?320|Fischsortieren [NOAA Photo Library, CC BY 2.0](([[https://www.flickr.com/photos/noaaphotolib/5102531763/|fish0191]] by  +<figure right>{{:p:pasted:fish0191.jpg?320}} 
-[[https://www.flickr.com/photos/noaaphotolib/|NOAA Photo Library]] on flickr, CC BY 2.0)) }}]+<caption>Fischsortieren [NOAA Photo Library, CC BY 2.0](([[https://www.flickr.com/photos/noaaphotolib/5102531763/|fish0191]] by  
 +[[https://www.flickr.com/photos/noaaphotolib/|NOAA Photo Library]] on flickr, CC BY 2.0))</caption></figure>
  
 👩‍🦰 Erinnerst du dich an Sigrún, welche vor Island auf einem Hochseeschiff die beiden Fischsorten Hering und Lodde bei Wind und Wetter von Hand sortieren musste (siehe nebenstehende Abbildung)? Du hattest ihr geholfen, mithilfe eines neuronalen Netzes einen Fischsortierapparat zu entwickeln. Diese Seite fasst das Wichtigste noch einmal zusammen.  👩‍🦰 Erinnerst du dich an Sigrún, welche vor Island auf einem Hochseeschiff die beiden Fischsorten Hering und Lodde bei Wind und Wetter von Hand sortieren musste (siehe nebenstehende Abbildung)? Du hattest ihr geholfen, mithilfe eines neuronalen Netzes einen Fischsortierapparat zu entwickeln. Diese Seite fasst das Wichtigste noch einmal zusammen. 
  
-⚠️ Solltest du dich nicht mehr daran erinnern (oder dieses Abenteuer noch nicht durchlebt haben) so raten wir dir, die vierteilige Story [[:p:ki:fische1|🐟 Künstliche Intelligenz für echte Fische]] durchzuarbeiten (ca. 45 Minuten) und anschliessend weiter unten mit Kapitel "4. Spezialfälle" weiterzufahren.+⚠️ Solltest du dich nicht mehr daran erinnern (oder dieses Abenteuer noch nicht durchlebt haben) so raten wir dir, die ersten 4 Teile der Story [[:p:ki:fische1|🐟 Künstliche Intelligenz für echte Fische]] durchzuarbeiten (ca. 45 Minuten) und anschliessend weiter unten mit Kapitel "4. Spezialfälle" weiterzufahren.
  
-| [{{:p:pasted:clupea_harengus1.jpg?320|Hering [Citron, Public Domain](([[https://commons.wikimedia.org/wiki/File:Clupea_harengus1.jpg|Clupea harengus]] by [[https://commons.wikimedia.org/wiki/User:Citron|Citron]] on wikimedia, Public Domain))}}] | [{{:p:pasted:mallotus_villosus.gif?320|Lodde [Fb78, Public Domain](([[https://commons.wikimedia.org/wiki/File:Mallotus_villosus.gif|Mallotus villosus]] by [[https://commons.wikimedia.org/wiki/User:Fb78|Fb78]] on wikimedia, Public Domain))}}] |+<figure center> 
 +<subfigure>{{:p:pasted:clupea_harengus1.jpg?320}}<caption>Hering [Citron, Public Domain](([[https://commons.wikimedia.org/wiki/File:Clupea_harengus1.jpg|Clupea harengus]] by [[https://commons.wikimedia.org/wiki/User:Citron|Citron]] on wikimedia, Public Domain))</caption></subfigure> 
 +<subfigure>{{:p:pasted:mallotus_villosus.gif?320}}<caption>Lodde [Fb78, Public Domain](([[https://commons.wikimedia.org/wiki/File:Mallotus_villosus.gif|Mallotus villosus]] by [[https://commons.wikimedia.org/wiki/User:Fb78|Fb78]] on wikimedia, Public Domain))</caption></subfigure> 
 +<caption>Die Fische in diesem Kapitel</caption> 
 +</figure>
  
 ~~INTOC~~ ~~INTOC~~
  
 ===== - Daten zusammenstellen ===== ===== - Daten zusammenstellen =====
-[{{ :p:pasted:fischsamples.png?150px|Vermessene Fische((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) }}]+<figure right>{{:p:pasted:fischsamples.png?150px}}<caption>Vermessene Fische((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) </caption></figure>
 Der Fischsortierapparat unterscheidet Hering und Lodde aufgrund mehrerer Messgrössen der Fische (z.B. Gewicht, Länge, Lichtreflexivität etc.). Für den Erfolg des Apparats ist die Auswahl dieser Messgrössen entscheidend. Wenn die Messgrössen schlecht gewählt sind, können die Fischsorten nicht oder nur schlecht voneinander getrennt werden und jeder noch so „intelligente“ Apparat wird versagen. Ebenso müssen alle "Varianten" einer jeden Fischsorte in den Daten berücksichtigt werden (z.B. kleine, mittlere und grosse Fische). Wird der Apparat z.B. nur auf grosse Fische geeicht, so wird dieser bei kleinen Fischen versagen. Der Fischsortierapparat unterscheidet Hering und Lodde aufgrund mehrerer Messgrössen der Fische (z.B. Gewicht, Länge, Lichtreflexivität etc.). Für den Erfolg des Apparats ist die Auswahl dieser Messgrössen entscheidend. Wenn die Messgrössen schlecht gewählt sind, können die Fischsorten nicht oder nur schlecht voneinander getrennt werden und jeder noch so „intelligente“ Apparat wird versagen. Ebenso müssen alle "Varianten" einer jeden Fischsorte in den Daten berücksichtigt werden (z.B. kleine, mittlere und grosse Fische). Wird der Apparat z.B. nur auf grosse Fische geeicht, so wird dieser bei kleinen Fischen versagen.
  
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-Das von uns verwendete neuronale Netz((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]]))</WRAP+<caption>Das von uns verwendete neuronale Netz((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]]))</caption></figure
-[{{ :p:pasted:decisionboundaries2.png?347px|Decision Boundaries((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) }}]+ 
 +<figure right>{{:p:pasted:decisionboundaries2.png?347px}}<caption>Decision Boundaries((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) </caption></figure>
  
 Das von uns verwendete neuronale Netz besitzt zwei Input Neuronen, mehrere Hidden Neuronen und ein Output Neuron. Die beiden Eingangsgrössen der Fische werden links in die beiden Input Neuronen eingegeben, als Resultat wird rechts vom Output Neuron eine Zahl zwischen 0 und 1 ausgegeben. Das von uns verwendete neuronale Netz besitzt zwei Input Neuronen, mehrere Hidden Neuronen und ein Output Neuron. Die beiden Eingangsgrössen der Fische werden links in die beiden Input Neuronen eingegeben, als Resultat wird rechts vom Output Neuron eine Zahl zwischen 0 und 1 ausgegeben.
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 ===== - Resultate einordnen ===== ===== - Resultate einordnen =====
  
-[{{ p:pasted:classoverlap.png?185px|Überlappende Klassen((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) }}]+<figure right>{{p:pasted:classoverlap.png?185px}}<caption>Überlappende Klassen((eigene Darstellung, [[https://creativecommons.org/publicdomain/zero/1.0/deed.de|CC0 1.0]])) </caption></figure>
 Du hattest mit dem Fischsortierapparat, der zwischen Hering und Lodde unterscheidet, eine Klassifikationsrate von rund 90% erreicht. Das hört sich nach viel an, jedoch sind 10% falsche Fische für Sigrún unbrauchbar. Du hattest mit dem Fischsortierapparat, der zwischen Hering und Lodde unterscheidet, eine Klassifikationsrate von rund 90% erreicht. Das hört sich nach viel an, jedoch sind 10% falsche Fische für Sigrún unbrauchbar.
  
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 === Daten === === Daten ===
   * **Relevante Eingangsgrössen:** Welche und wie viele Eingangsgrössen braucht es? Bei unpassenden Eingangsgrössen versagt jedes Verfahren. Z.B. lassen sich mit den Schweizer-Lottozahlen kaum Fische unterscheiden.   * **Relevante Eingangsgrössen:** Welche und wie viele Eingangsgrössen braucht es? Bei unpassenden Eingangsgrössen versagt jedes Verfahren. Z.B. lassen sich mit den Schweizer-Lottozahlen kaum Fische unterscheiden.
-  * **Umfassende Daten:** Es braucht Daten, welche alle möglichen, relevanten Fälle beinhalten. Wenn Fälle im Training fehlen, so produziert das Verfahren anschliessend für diese Fälle unsinnige Antworten. Z.B. versagt eine Fischklassifikation für kleine Fische, wenn diese nur mit grossen trainiert wurde.+  * **Umfassende Daten:** Es braucht Daten, welche alle möglichen, relevanten Fälle beinhalten. Wenn Fälle im Training fehlen oder in einer zu geringen Anzahl vorkommen, so produziert das Verfahren anschliessend für diese Fälle unsinnige oder einseitige Antworten. Z.B. versagt eine Fischklassifikation für kleine Fische, wenn diese nur mit grossen trainiert wurde.
   * **Genügend viele Daten:** Wenn zu wenige Daten vorhanden sind, so besteht die Gefahr eines Auswendiglernens, d.h. die Gefahr von Overfitting.    * **Genügend viele Daten:** Wenn zu wenige Daten vorhanden sind, so besteht die Gefahr eines Auswendiglernens, d.h. die Gefahr von Overfitting. 
  
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   * **Überlappende Muster:** Besitzen mehrere zu unterscheidende Datenpunkte dieselben oder genügend ähnliche Eingangsgrössen, so können diese nicht verlässlich unterschieden werden. Überlappende Muster treten in praktisch allen nicht künstlich erzeugten Datensätzen auf.   * **Überlappende Muster:** Besitzen mehrere zu unterscheidende Datenpunkte dieselben oder genügend ähnliche Eingangsgrössen, so können diese nicht verlässlich unterschieden werden. Überlappende Muster treten in praktisch allen nicht künstlich erzeugten Datensätzen auf.
   * **Seltene Muster:** Seltene Muster (oder seltene Ereignisse) werden tendenziell von den Verfahren ignoriert. Verlässliche Gegenmassnahmen sind bis dato nicht bekannt.   * **Seltene Muster:** Seltene Muster (oder seltene Ereignisse) werden tendenziell von den Verfahren ignoriert. Verlässliche Gegenmassnahmen sind bis dato nicht bekannt.
 +  * **Transparenz:** Aufgrund des Blackbox-Charakters der gängigen KI-Verfahren, kann weder vernünftig erklärt noch begründet werden, warum eine KI bei der Eingabe X die Ausgabe Y produziert.
 +  * **Bias:** Unausgewogene Trainingsdaten, seltene oder fehlende Muster führen zu einseitigen oder unsinnigen Antworten. Dieses Verhalten wird als "Bias" bezeichnet. Z.B. sind KI-Chatbots nicht "neutral" in ihren Aussagen, da die zugrundeliegenden Trainingsdaten (mehrheitlich Texte aus dem Internet) auch nicht "neutral" sind.
  
 ==== Fazit ====  ==== Fazit ==== 
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 ++++Unsere Einschätzung|KI-Systeme wie die Fischklassifikation oder KI-Chat-Anwendungen können erstaunlich gute Resultate liefern, da ist sehr wahrscheinlich noch viel zu erwarten. Jedoch werden solche Systeme auch in Zukunft praktisch nie völlig fehlerfrei arbeiten und warum ein solches System etwas entscheidet, oder ausgibt, werden wir vermutlich auch in Zukunft nicht vollständig nachvollziehen können.\\ \\  ++++Unsere Einschätzung|KI-Systeme wie die Fischklassifikation oder KI-Chat-Anwendungen können erstaunlich gute Resultate liefern, da ist sehr wahrscheinlich noch viel zu erwarten. Jedoch werden solche Systeme auch in Zukunft praktisch nie völlig fehlerfrei arbeiten und warum ein solches System etwas entscheidet, oder ausgibt, werden wir vermutlich auch in Zukunft nicht vollständig nachvollziehen können.\\ \\ 
-Wir Menschen wählen Daten, Eingangsgrössen, Verfahren, Anzahl Gewichte, Fehlerwerte und Thresholds aus. Wir Menschen bestimmen, wie mit den Resultaten, die eine KI produziert, umgegangen wird. Somit sind wir für unsere KIs auch verantwortlich.+++++Wir Menschen wählen Daten, Eingangsgrössen, Verfahren, Anzahl Gewichte, Fehlerwerte und Thresholds aus. Wir Menschen bestimmen, wie mit den Resultaten, die eine KI produziert, umgegangen wird. Somit sind wir für unsere KIs und deren Bias auch verantwortlich.++++
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