“Look what the hardware people have managed to do with Moore’s Law. Now it’s going to be software’s turn.”

Everyone’s a ProgrammerSoftware is collapsing under the weight of its own complexity. Charles Simonyi’s solution? Programming tools that are so simple that even laypeople can use them.

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How thinking happens: Triangulation

The term "rearranging"

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Accelerating Scientific Discovery by Lowering Barriers toUser-Generated Synthesis of Scientific Literature

Procedural Programming: It’s Back? It Never Went Away - Kevlin Henney [ACCU 2018]

Intentional Programming Last updated: August 18, 2011

The History of Microsoft -- The Charles Simonyi Story (Part 2 of 2)

it's too bad that the system cannot come up automatically with a meaningful name so we have to supply that writing a new enzyme is not very hard using ip's

can extract a procedure from open code we start by selecting a piece of code that we think might be shareable we apply the enzyme and we get a procedure and a call to it with all the necessary

given that the program is a database it's easy to create tools that operate on programs because we like biological metaphors we call these tools enzymes there is an IP a very useful enzyme that

existential opportunity for establishing a world ‘goodenough’ for humans to live in.

Our proposition is grounded in a detailed analysis of themanner in which the socio-econo-political system has evolved into a powerful control mechanismthat subsumes human minds, steers their will and automates their thinking.

serving to augment the autonomy of the first from the‘programming’ imposed by the second.

hree kinds of cognitive system—the human mind, social systemsand the emerging synthetic intelligence

It will becomea distributed, synthetically intelligent agent in itself

mediate theexecution of contracts, transactions, public interventions and all other change-establishing eventsmore reliably and more synergistically than any other technology or institution

call to action

we start from the bottom and build tools for people to adopt and then you grow the infrastructure

subscribe to graph queries you can start there

revising a larger vision we have this building block for a new infrastructure beyond itunes for papers and 00:43:30 yeah we start by just facilitating collaboration systems and then you can scale up by prioritizing decentralization and federation and we can publish to say databases like ceramic or the graph or so on and people 00:43:43 can subscribe to graph queries you can start there as opposed to every publishing into a single stream immediately to have people talk to each other i like this metaphor uh the way that we're working as opposed to starting from the top and saying

some point we need some way to 00:43:05 understand which pieces of evidence are the same or similar which pieces of claims are similar or not

middle layer between the sort of more structured knowledge graph that's more granular and the more coarse documents this kind of middle layer the 00:42:52 disco stuff could enable sort of communication across the systems

translating between 00:42:03 user extendable grammars but also having a similar underlying idea seems like one promising way to enable this peer-to-peer thing to start people might be concerned about formality machine readability

avoid the one standard problem

we have a proven concept it's possible to write close to probes and create shareable discourse graphs as 00:41:12 a byproduct uh i think this opens up new pops the sustainable scalable authoring

enables you to sort of translate between those 00:41:00 this is a bigger promising design pattern

ery minimal ontology of questions and evidence and you can extend it in lo

extending or personalizing grammar is crucial right many extensions were finer distinctions right we have different flavors of claims or different 00:40:34 flavors of evidence but you can also be collapsed together if you wanted to sort of translate to a different graph and this connects to this kind of concept of boundary objects from information science

using it to find and access important ideas like later on they can use the more advanced features but uh just simply having the discourse graph as a way to structure right that model 00:40:22 is a way to structure it thinking

fostering more careful and career thinking patterns was most of the time enough for people to adopt this they wanted to think in this way and the tool helps them to think in this way and 00:40:11 that's that's good

some efforts to port this discourse graph to an html annotation standard for broader web publishing use

the way that the system knows how to translate the writing patterns into edges is through a grammar that is user customizable that essentially says 00:35:14 when i write something like this which is on the left i want you to save it and recognize it that this is a particular relationship right

if you force people to only think in terms of structured nodes 00:32:55 and edges for example it sort of kills the thinking process

integrate that into the the document itself

you're looking for papers but really what you care about is what's in them the ideas the claims the arguments the theories the findings and the discourse relations between the 00:05:08 right support opposition replication lines of evidence lines of contradiction right these kinds of things

these indexing systems work with what they have the data 00:05:59 structure is what's at issue similarly um we have entire industry of system review tools and processes that are essentially dedicated to working against the underlying data structure they are sort of like we've got these 00:06:12 papers and we need to work our way around it so we have all these processes for screening for data extraction to get to the thing we actually care about and then we don't share anybody else and everybody has to start from scratch next time

theory is evidence problem solutions they're not first-class citizens

core conjecture of this line of work is that it's not just about the tools it's not just about our motivation it's about the infrastructure it's about the unit of analysis right why why does google scholar work

accelerating scientific discovery by lowering barriers to 00:00:42 user-generated synthesis of scientific literature which will include discussing how scholarly practices could be transformed

f feeding its slave to the trap data you have this sense that um of fighting against uh the infrastructure

synthesis is actually really hard

risk wasting our time on questions that are trivial impossible misframed one of my favorite phrases is you can't play 20 questions with nature and win

a recent nobel prize winner who credited some of her key inspirations to a masterful survey of the literature in a handbook chapter of economic developmental economics and 00:02:11 it really laid out some key problems in the field that she was able to sort of connect with her expertise and experimental methods

giving insight into here are some of the gaps here are where we should be going next um driving progress forward

key intuition is that you create a new innovative conceptual whole that's greater than the sum of the parts of things that you're integrating

so what i mean by synthesis it's probably an intuitive concept but some examples include theories models design spaces and very good systematic or literature reviews

goal is to remove various defective synthesis

update on what i talked about in the previous talk which was linked in the chat

it’s a challenge to get users to input metadata in a consistent way

is limited by its inability to be queried and updated.

How can we build upon implicit metadata for a frictionless user experience?

Research Grant Application

physical systems can be completely deterministic and yet still be inherently unpredictable

As a graduate student in Chihiro Hayashi's laboratory at Kyoto University, Yoshisuke Ueda was experimenting with analog computers and noticed, on November 27, 1961, what he called "randomly transitional phenomena". Yet his advisor did not agree with his conclusions at the time, and did not allow him to report his findings until 1970

Bret Victor - The Humane Representation of Thought

"You can’t play twenty questions with nature and win"

scientific progress may not even be tractable without adequatesynthesis (as theory), even with advanced methods and data

especially necessary for problems where it is difficult orimpossible to construct decisive experimental tests

Synthesis maybe supported by and manifested in a variety of forms, such as a theory, an effective systematic or inte-grative literature review, a causal model, a cogent research proposal or problem formulation, or model ofa design space, among others.

Effective synthesis generates new knowledge, integrating relevant theories, concepts, claims, andevidence into novel conceptual wholes [Strike and Posner, 1983, Blake and Pratt, 2006].

To advance science, scientists must synthesize what is currently known and unknown

WordNet # (n) bon mot a clever remark

Pseudonymous Credibility without public identity.

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