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Full Summary of Law and Technology

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This is a complete summary of Law and Technology. The course is taught in English, making some pros almost unintelligible. Contents: lesson notes, powerpoint, extra info from the handbook and all relevant articles

Preview 6 out of 145  pages

  • December 29, 2022
  • 145
  • 2022/2023
  • Summary

1  review

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By: fleurbogaert • 9 months ago

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law and technology
1) technology
1.1) information technology
= use of computers to store, retrieve and exchange all kinds of date
→ scientific discipline: computer science = in almost every curriculum

example big date science 1890
→ hollerith tabulator = used in US for calculating the population

every 10 years by hand, because it took them 10 years to proces the information

this advice could operate this way faster = counting + punch card (punching
holes in paper card) = data records

database = collection of data records

it could make local processing easier + cheaper

⇒ he also founded the CTR = renamed in 1924 to IPN, which still exists today
history

pre-mechanical (3000 BC - 1450 AD)

mechanical (1450 - 1840)

electromechanical (1840 - 1940)

electronic (1940 - present)

hardware and software

bv self-driving car: car + AI (deep learning, …)

hardware = physical parts

screen, memory, motherboard

software = instructions and codes that are needed to make the hardware work
(basic and advanced)

algorythm = software that fulfills a certain function (bv Bubblesort = to sort a
list of numbers by taking each time a pair of numbers to sort until you get the
right order)



law and technology 1

, essential building block of all software

works like a recipe → a finite sequince of instructions that describe
how to realise a specific goal

computer program = specific implementation of such an algorythm,
taking into account certain constraints such as specific programming
language

pseudocode = easier to understand as a norma person and this has
to be converted into something to make the computer work

typically organised hierarchically

user → applications software (app) → operating system (IOS,…) →
hardware

other aspects

local (my own computer) vs cloud based solution (connection of
computers)

open source (available for everybody, changeable) vs closed source
software (not changeable)

1.2) internet technology
= very large connection of computers via a common set of protocols

→ devices communicate via small packages that are sent around using IP/TCIP

Transmission Control Protocol/Internet Protocol

protocol to send around packages to communicate

→ you can have your own private internet = intranet

→ most of them are public

advantages

charing of information: through common protocols bv email, telephony

changed the way of communication completely bv social networks, TV,…

access to the internet: provided by ISP (bv proximus)

network hardware bv switches, routers, cables, servers, printers = all connected to
the same network

challenges of internet


law and technology 2

, novel types of crime bv fraude, fake news

creates social disparity (internet illiteracy) = some people do not understand new
technologies

dealing with private and sensitive information bv monitoring-cameras

⇒ new playground for lawyers!!!
WWW

°1989 by sir Tim-berners-Lee

collection of documents, linked by a protocol (HTTP)

HTTP builds further on IP = determents on which server the document is
resting

every document is characterised by the URL

web browsers translates URL into IP adresses

makes use of domain name system (DNS)

web pages are formatted in HTML = programming language (set of commands)

internet of things (IoT)

many small devices all connected through communications protocols (bv
sensors, camera’s)

protocols are often determined by physical distance bv bluetooth, 5G

the cloud = large group of computers to proces a large amount of information →
processing en data warehouse

the edge = real time data processing, local processing

edge computing = allows data to go from IoT to be analysed by the edge to go to
the cloud

big data and cloud computing

many devices = continuously generating info that needs to be processed to find
interesting patterns

large amounts of date = cannot be handled by a single machine

we need scalable infrastructures and computing paradigms to make use of these
data




law and technology 3

, → big data science = refers to data-mining problems the volume, diversity and
complexity of which requires the development of novel techniques etc to extract
valuable knowledge that is typically hidden inside data

→ makes use of cloud computing = large-scale distributed computing resources

fault tolerance built-on = if a server breaks down, you can still process because
another server takes over

less vulnerable to hardware crashes

abstracts away a lot of the hardware issues for end user = makes it easier for us

flexible cost: you pay as much as you consume

various types

end user → SAAS (software) bv gmail

software developers → PAAS (platform) bv Google app

network architects → IAAS (infrastructure) bv Google compute engine

charateristics of big data science systems

data contains value and knowledge

5V’s

variety: dealing with different types of data (structued/unstructureed)→ how
to use data to create a bigger picture

veracity: we cannot always control the quality/accuracy of data → data may
be missing etc

value: most importent motivation → better models, insights, new
opportunities

volume: data generated every second and this has become to big to store
traditionally → big data can store this using distributed systems

velocity: speed at which data is generated + data needs to be analysed +
decisions need to be taken

application areas

science and research

healthcare and public health

business and comerce



law and technology 4

, economy and sustainability



1.3) cryptography, blockchain and cryptocurrency
enhancing trust
→ cryptocraphy = mathematical techniques that allow for encryption and decryption
of messages
→ used in financial applications

public-key crypthography

public: accesible to everyone

private: only known to the owner

key generation = based on cryptographic hash functions (Y=X → easy to
calculate Y given X but hard to find X, given Y)

security = difficalt to attack (only brute-force)



💡 secure communication using PK cyptograpghy

bob takes the public key from alice and uses this to encrypt a
message

the message transfers over insecure communication channels

alice decrypt the message with her private key

secure athentication bv signing protocol: signed with private key but verify
with public key



blockchain and cryptocurrencies

motivation: need for a decentralised system, that allows for valid electronic
financial activity → replaces classical banks

storing personal information, service transferring, transaction managment by
tracking transactions

identity managment bv proof of spending

prevention of theft




law and technology 5

, B = special database of transactions

can be used for many applications

smart contracts: encode agreements in software instead of natural language

any action is done bu requesting the execution of a function

supply chain track

1.4) AI
motivating examples

smart planners

facial recognition

reccomander systems

will AI be everywhere? experts predict it will be used more often

imitation game 1950 (Turing)
→ test = system to control if a computer is intellegent or not

human interrogator, a human and an AI system: the interrogator has to know
who answers

goals AI

process natural language

learn from conversation

memorize what has been said before

communicate back

have an idea of common sense

has become better and better

current state of the art: you can ask questions and you get answers back from
the system

AI ingedients

input → processing → output

reasoning and planning

learn/adapt = memory and simulate



law and technology 6

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