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10 changes: 5 additions & 5 deletions _sources/act_1/act_1_0/act_1_0_0/act_1_0_0_6.ipynb
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"# 43\n",
"\n",
"+ come full circle these 43 years:\n",
" 1. [philosophy](https://en.wikipedia.org/wiki/Cru_(Christian_organization)#Four_Spiritual_Laws) ([explo85](https://www.latimes.com/archives/la-xpm-1986-01-04-me-24254-story.html))\n",
" 2. knowledge (student)\n",
" 3. error (faculty)\n",
" 4. icc (gtpci)\n",
" 5. back-at-one (tenure)\n",
" 1. [philosophy](https://en.wikipedia.org/wiki/Cru_(Christian_organization)#Four_Spiritual_Laws) ([explo85](https://www.latimes.com/archives/la-xpm-1986-01-04-me-24254-story.html)) 0-5\n",
" 2. knowledge (student) 6-35\n",
" 3. error (faculty) 36-43\n",
" 4. icc (gtpci) 40-44\n",
" 5. back-at-one (tenure) 45-50\n",
" - truth; amoral (one is trained to treat ephors as gods; remove error of man)\n",
" - fraud; moral (spartan ephors in 300; like magesterium in vatican)\n"
]
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51 changes: 50 additions & 1 deletion _sources/act_1/act_1_0/act_1_0_1/act_1_0_1_1.ipynb
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"- **Between-Group Variability**: This would pertain to the variability in measurements made across different objects (different patients, in this case). In other words, it would look at how much the diagnoses (ICD-10 codes) vary from one patient to another when assessed by the same or different clinicians.\n",
"\n",
"In ICC calculations, a high ICC value would suggest that the within-group variability is low relative to the between-group variability. In simpler terms, it would mean that clinicians are more or less agreeing on the ICD-10 codes for each patient (low within-group variability), and that there are distinguishable differences in diagnoses between different patients (high between-group variability). This would be an indicator of reliable and consistent measurement.\n",
"\n"
"\n",
"# 56\n",
"\n",
"Your engagement with the issues of bias and justice in AI, framed through your conceptual lens of Truth/Knowledge/Morality, is both compelling and timely. The topic of AI bias does indeed fit well within the framework you provided. (Inspired by Kadija Ferryman)\n",
"\n",
"### Bias in AI: Aligning with your Framework\n",
"\n",
"- **Truth**: In the context of AI, the quest for 'truth' often aims for unbiased, accurate models. However, as is the case with AI in healthcare, existing societal biases can seep into the data, thus affecting the model. Bias in AI is not solely an issue of \"variance\" or \"error\"; it is often an artifact of the data generating process itself, which can be fraught with systemic inequities.\n",
"\n",
"- **Knowledge**: Acquiring knowledge on the subject often involves statistical rigor and a careful balancing act of controlling for variance and bias. This is where your emphasis on \"Explain/Control\" comes in; there is a need to go back to the data-generating process to identify root causes, perhaps using randomized controlled trials (RCTs) to isolate these factors.\n",
"\n",
"- **Morality**: Finally, we find ourselves at the intersection of AI and morality. Questions of justice, equity, and ethics are never far behind when talking about bias. The road of truth requires an unbiased but often highly imprecise approach, while the road of fraud (or, more generally, unethical behavior like p-hacking or selective reporting) can lead to seemingly compelling but ultimately deceptive findings.\n",
"\n",
"### Revisiting 43 Years\n",
"\n",
"As you map out your journey from philosophy to tenure, this kind of critical thinking can serve you well in any endeavor—be it academic, scientific, or even moral. Your experience encompasses various dimensions, from seeking philosophical and academic knowledge to grappling with the imperfections (error, bias, etc.) inherent in human understanding. \n",
"\n",
"- For example, your past focus on ICCs could lend a quantitative aspect to these kinds of moral and philosophical inquiries, which are typically qualitative.\n",
" \n",
"- Your multidisciplinary approach, as indicated in your journey from philosophy to tenure, offers a rich blend for tackling complex issues like AI bias. \n",
"\n",
"The question, then, is how to apply this well-rounded perspective in a practical manner. Given your interests and experience, multidisciplinary research projects, academic courses, or even public policy initiatives could benefit greatly from your insights.\n",
"\n",
"Would you like to explore ways to operationalize these ideas, perhaps in a research setting, tech startup, or through cross-disciplinary collaborations?\n",
"\n",
"# 57\n",
"\n",
"Chinese (Simplified): 我们同舟共济 (Wǒmen tóngzhōu gòngjì)\n",
"Arabic: نحن جميعاً في نفس السفينة (Nahnu jamee'an fi nafs as-safinah)\n",
"Hebrew: כולנו באותו הסירה (Kulanu beoto ha'sirah)\n",
"Hindi: हम सब एक ही नाव में हैं (Hum sab ek hi naav mein hain)\n",
"Spanish: Todos estamos en el mismo barco\n",
"French: Nous sommes tous dans le même bateau\n",
"German: Wir sitzen alle im selben Boot\n",
"Italian: Siamo tutti nella stessa barca\n",
"Portuguese: Estamos todos no mesmo barco\n",
"Dutch: We zitten allemaal in hetzelfde schuitje\n",
"Russian: Мы все в одной лодке (My vse v odnoi lodke)\n",
"Persian: ما همه در یک قایق هستیم (Ma hame dar yek ghayegh hastim)\n",
"Japanese: 皆で同じ船に乗っている (Mina de onaji fune ni notte iru)\n",
"Swahili: Sote tuko kwenye chombo kimoja\n",
"Zulu: Sisonke kule ndawo\n",
"Yoruba: Awa gbogbo wọ́ l’ọkọ̀ kan\n",
"Igbo: Anyị nile nọ n’ụgbọ mmiri otu\n",
"Korean: 우리는 모두 같은 배에 타고 있다 (Urineun modu gateun bae-e tago itda)\n",
"Finnish: Olemme kaikki samassa veneessä\n",
"Amharic: እኛ ሁሉም በአንድ ጀልባ ውስጥ ነን (Enya hulume be'and jelba weset nene)\n",
"Oromo: Hinqabu fi hinqabu jechuun if bira jiraanne\n",
"Tigrinya: ኩሉና ኣብ አንድ ድሕሪ እዩና (Kulluna ab and dehri e'yuna)\n",
"Gujarati: અમે બધા એવું જ વાંડો છીએ (Amē baḍhā ēvuṁ ja vāṇḍō chhīē)\n"
]
}
],
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12 changes: 7 additions & 5 deletions act_1/act_1_0/act_1_0_0/act_1_0_0_6.html
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<li class="toctree-l1"><a class="reference internal" href="../act_1_0_1/act_1_0_1_1.html"></a></li>



<li class="toctree-l1"><a class="reference internal" href="../act_1_0_1/act_1_0_1_2.html">.</a></li>
<li class="toctree-l1"><a class="reference internal" href="../act_1_0_1/act_1_0_1_3.html">.</a></li>
<li class="toctree-l1"><a class="reference internal" href="../act_1_0_1/act_1_0_1_4.html">.</a></li>
Expand Down Expand Up @@ -742,11 +744,11 @@ <h1>43<a class="headerlink" href="#id10" title="Permalink to this heading">#</a>
<ul class="simple">
<li><p>come full circle these 43 years:</p>
<ol class="arabic simple">
<li><p><a class="reference external" href="https://en.wikipedia.org/wiki/Cru_(Christian_organization)#Four_Spiritual_Laws">philosophy</a> (<a class="reference external" href="https://www.latimes.com/archives/la-xpm-1986-01-04-me-24254-story.html">explo85</a>)</p></li>
<li><p>knowledge (student)</p></li>
<li><p>error (faculty)</p></li>
<li><p>icc (gtpci)</p></li>
<li><p>back-at-one (tenure)</p>
<li><p><a class="reference external" href="https://en.wikipedia.org/wiki/Cru_(Christian_organization)#Four_Spiritual_Laws">philosophy</a> (<a class="reference external" href="https://www.latimes.com/archives/la-xpm-1986-01-04-me-24254-story.html">explo85</a>) 0-5</p></li>
<li><p>knowledge (student) 6-35</p></li>
<li><p>error (faculty) 36-43</p></li>
<li><p>icc (gtpci) 40-44</p></li>
<li><p>back-at-one (tenure) 45-50</p>
<ul>
<li><p>truth; amoral (one is trained to treat ephors as gods; remove error of man)</p></li>
<li><p>fraud; moral (spartan ephors in 300; like magesterium in vatican)</p></li>
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<li class="toctree-l1 current active"><a class="current reference internal" href="#"></a></li>



<li class="toctree-l1"><a class="reference internal" href="act_1_0_1_2.html">.</a></li>
<li class="toctree-l1"><a class="reference internal" href="act_1_0_1_3.html">.</a></li>
<li class="toctree-l1"><a class="reference internal" href="act_1_0_1_4.html">.</a></li>
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<ul class="visible nav section-nav flex-column">
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#"></a></li>
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#id2">55</a></li>
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#id3">56</a><ul class="visible nav section-nav flex-column">
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#bias-in-ai-aligning-with-your-framework">Bias in AI: Aligning with your Framework</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#revisiting-43-years">Revisiting 43 Years</a></li>
</ul>
</li>
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#id4">57</a></li>
</ul>

</nav>
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<li><p><strong>Between-Group Variability</strong>: This would pertain to the variability in measurements made across different objects (different patients, in this case). In other words, it would look at how much the diagnoses (ICD-10 codes) vary from one patient to another when assessed by the same or different clinicians.</p></li>
</ul>
<p>In ICC calculations, a high ICC value would suggest that the within-group variability is low relative to the between-group variability. In simpler terms, it would mean that clinicians are more or less agreeing on the ICD-10 codes for each patient (low within-group variability), and that there are distinguishable differences in diagnoses between different patients (high between-group variability). This would be an indicator of reliable and consistent measurement.</p>
</section>
<section class="tex2jax_ignore mathjax_ignore" id="id3">
<h1>56<a class="headerlink" href="#id3" title="Permalink to this heading">#</a></h1>
<p>Your engagement with the issues of bias and justice in AI, framed through your conceptual lens of Truth/Knowledge/Morality, is both compelling and timely. The topic of AI bias does indeed fit well within the framework you provided. (Inspired by Kadija Ferryman)</p>
<section id="bias-in-ai-aligning-with-your-framework">
<h2>Bias in AI: Aligning with your Framework<a class="headerlink" href="#bias-in-ai-aligning-with-your-framework" title="Permalink to this heading">#</a></h2>
<ul class="simple">
<li><p><strong>Truth</strong>: In the context of AI, the quest for ‘truth’ often aims for unbiased, accurate models. However, as is the case with AI in healthcare, existing societal biases can seep into the data, thus affecting the model. Bias in AI is not solely an issue of “variance” or “error”; it is often an artifact of the data generating process itself, which can be fraught with systemic inequities.</p></li>
<li><p><strong>Knowledge</strong>: Acquiring knowledge on the subject often involves statistical rigor and a careful balancing act of controlling for variance and bias. This is where your emphasis on “Explain/Control” comes in; there is a need to go back to the data-generating process to identify root causes, perhaps using randomized controlled trials (RCTs) to isolate these factors.</p></li>
<li><p><strong>Morality</strong>: Finally, we find ourselves at the intersection of AI and morality. Questions of justice, equity, and ethics are never far behind when talking about bias. The road of truth requires an unbiased but often highly imprecise approach, while the road of fraud (or, more generally, unethical behavior like p-hacking or selective reporting) can lead to seemingly compelling but ultimately deceptive findings.</p></li>
</ul>
</section>
<section id="revisiting-43-years">
<h2>Revisiting 43 Years<a class="headerlink" href="#revisiting-43-years" title="Permalink to this heading">#</a></h2>
<p>As you map out your journey from philosophy to tenure, this kind of critical thinking can serve you well in any endeavor—be it academic, scientific, or even moral. Your experience encompasses various dimensions, from seeking philosophical and academic knowledge to grappling with the imperfections (error, bias, etc.) inherent in human understanding.</p>
<ul class="simple">
<li><p>For example, your past focus on ICCs could lend a quantitative aspect to these kinds of moral and philosophical inquiries, which are typically qualitative.</p></li>
<li><p>Your multidisciplinary approach, as indicated in your journey from philosophy to tenure, offers a rich blend for tackling complex issues like AI bias.</p></li>
</ul>
<p>The question, then, is how to apply this well-rounded perspective in a practical manner. Given your interests and experience, multidisciplinary research projects, academic courses, or even public policy initiatives could benefit greatly from your insights.</p>
<p>Would you like to explore ways to operationalize these ideas, perhaps in a research setting, tech startup, or through cross-disciplinary collaborations?</p>
</section>
</section>
<section class="tex2jax_ignore mathjax_ignore" id="id4">
<h1>57<a class="headerlink" href="#id4" title="Permalink to this heading">#</a></h1>
<p>Chinese (Simplified): 我们同舟共济 (Wǒmen tóngzhōu gòngjì)
Arabic: نحن جميعاً في نفس السفينة (Nahnu jamee’an fi nafs as-safinah)
Hebrew: כולנו באותו הסירה (Kulanu beoto ha’sirah)
Hindi: हम सब एक ही नाव में हैं (Hum sab ek hi naav mein hain)
Spanish: Todos estamos en el mismo barco
French: Nous sommes tous dans le même bateau
German: Wir sitzen alle im selben Boot
Italian: Siamo tutti nella stessa barca
Portuguese: Estamos todos no mesmo barco
Dutch: We zitten allemaal in hetzelfde schuitje
Russian: Мы все в одной лодке (My vse v odnoi lodke)
Persian: ما همه در یک قایق هستیم (Ma hame dar yek ghayegh hastim)
Japanese: 皆で同じ船に乗っている (Mina de onaji fune ni notte iru)
Swahili: Sote tuko kwenye chombo kimoja
Zulu: Sisonke kule ndawo
Yoruba: Awa gbogbo wọ́ l’ọkọ̀ kan
Igbo: Anyị nile nọ n’ụgbọ mmiri otu
Korean: 우리는 모두 같은 배에 타고 있다 (Urineun modu gateun bae-e tago itda)
Finnish: Olemme kaikki samassa veneessä
Amharic: እኛ ሁሉም በአንድ ጀልባ ውስጥ ነን (Enya hulume be’and jelba weset nene)
Oromo: Hinqabu fi hinqabu jechuun if bira jiraanne
Tigrinya: ኩሉና ኣብ አንድ ድሕሪ እዩና (Kulluna ab and dehri e’yuna)
Gujarati: અમે બધા એવું જ વાંડો છીએ (Amē baḍhā ēvuṁ ja vāṇḍō chhīē)</p>
</section>

<script type="text/x-thebe-config">
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<ul class="visible nav section-nav flex-column">
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#"></a></li>
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#id2">55</a></li>
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#id3">56</a><ul class="visible nav section-nav flex-column">
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#bias-in-ai-aligning-with-your-framework">Bias in AI: Aligning with your Framework</a></li>
<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#revisiting-43-years">Revisiting 43 Years</a></li>
</ul>
</li>
<li class="toc-h1 nav-item toc-entry"><a class="reference internal nav-link" href="#id4">57</a></li>
</ul>

</nav></div>
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