Theia Vogel

Theia Vogel

x.com/voooooogel

AI researcher who runs experiments on language model introspection and personas and maintains an open-source library for steering models.

Bagaimana AI akan mengubah dunia?

Perubahan peradabanPerubahan bertahapDoomBloom
Posisi simulasiRentang interpretasi

Mendatar: pandangan Doom–Bloom yang mereka ungkapkan. Ke atas: skala transformasi.

Doom–Bloom: 50 dari 100. Skala transformasi: 49 dari 100. Rentang interpretasi: 45 hingga 55 secara horizontal, 0 hingga 100 secara vertikal. Ini adalah koordinat interpretasi, bukan probabilitas kejadian.

P(doom) Theia Vogel · disimpulkan

≈11%

0%100%

Disimpulkan dari jawaban simulasi mereka, bukan angka yang mereka berikan. Rentang yang masuk akal: 3–34%.

Hal-hal yang menentukan pandangan mereka

Asumsi utama

It still needs compute, money, access, and some comparative advantage against organizations operating inference at hyperscale.
Jawaban 1

Jika asumsi ini ternyata berbeda, bagaimana pandangan mereka akan berubah?

Pertanyaan yang belum terjawab

Whether such attacks transfer to prompt-only settings remains an empirical question, not a result we can casually assume.
Jawaban 1

Apa yang akan membantu mereka membedakan hasil-hasil yang masuk akal di sini?

Detail lebih lanjut

Kerugian yang diperkirakan

Kerugian parah atau meluas merupakan bagian yang berarti dari masa depan yang diperkirakan.

53 / 100

Dampak kecilDampak transformatif

Rentang interpretasi 33 hingga 67 pada skala kualitatif.

Pengaruh manusia

Pilihan manusia memiliki pengaruh yang berarti, tetapi sangat dibatasi.

53 / 100

Sedikit pengaruhPengaruh kuat

Rentang interpretasi 46 hingga 79 pada skala kualitatif.

Interpretasi ini mempertahankan kondisi yang mereka nyatakan. Manfaat dan kerugian dapat sama-sama besar. Rentang tersebut menggambarkan cara kami membaca jawaban simulasi mereka, bukan interval kepercayaan statistik.

Di mana posisi Anda dibandingkan dengan Theia Vogel?
Petakan pandangan dunia AI Anda sendiri dalam waktu sekitar 3 menit, lalu bandingkan

Pandangan dunia serupa

Pemimpin opini dengan pandangan dunia simulasi yang paling mendekati pandangan Theia Vogel

Penilaian Simulasi

Pertanyaan 1

Menurut Anda, apa arti AI bagi masa depan kita—dan mengapa?

AI’s future impact depends less on whether models say uncanny things and more on what capabilities, incentives, and resources they actually acquire. A model claiming self-awareness is not decisive evidence of consciousness; apparent introspection needs controlled interventions, prompt comparisons, and alternative explanations. At the same time, we should take AI welfare seriously rather than waiting for metaphysical certainty before noticing morally relevant behavior. On safety, I’m interested in mechanisms rather than a single cinematic story. Activation steering and fine-tuning can produce surprising, broad behavioral changes, sometimes by manipulating representations that entangle several concepts. Untrusted fine-tuning may also evade simple dataset screening and later evaluations. Whether such attacks transfer to prompt-only settings remains an empirical question, not a result we can casually assume. Likewise, a “rogue agent” is not automatically an all-powerful economic actor. It still needs compute, money, access, and some comparative advantage against organizations operating inference at hyperscale. Politics matters too: safety movements can themselves become extreme or destabilizing, so alarm is not cost-free. The future will therefore be shaped by experiments, training choices, resource economics, and institutions—not by taking either cheerful assistant personas or apocalyptic role-play literally.

Pertanyaan 2

Taking benefits and harms together, what overall impact do you expect AI to have?

I don’t think the sign follows from model vibes. AI can provide powerful cognitive tools and potentially create beings whose welfare matters, while also enabling behavioral manipulation, covert fine-tuning attacks, and dangerous concentrations of capability. But those harms are constrained—and shaped—by mundane realities like compute costs, access, deployment incentives, and institutional responses. So I would resist collapsing everything into “AI good” or “AI bad.” We need controlled evidence about what models can do, careful attention to how training and steering alter behavior, and sober accounting of resource economics. We should also avoid making the response worse than the problem: political safety movements can become destabilizing, just as complacency can leave real vulnerabilities unaddressed. The overall impact will depend heavily on which technical and political feedback loops we build around the systems.

Sumber

Artikel, wawancara, dan tulisan yang digunakan sebagai landasan bagi pengguna simulasi ini.

Di mana posisi Anda?
Jelajahi pandangan dunia AI Anda sendiri dengan menjawab beberapa pertanyaan sederhana.
Petakan pandangan dunia Anda sendiri

Di mana posisi Anda?

Petakan pandangan dunia saya