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University of Calgary
Management Information Systems
MGIS 317
Sharaz Khan

Week 9, Part 1 – Privacy, Security, Ethics, and Social Media  Julius Baer vs. WikiLeaks. Hard to sue WikiLeaks + harder to shut it down. Revise practices to avoid being targeted.  Ethics = moral duty/obligation. Individual values + org. policies + cultural norm/values = standards to guide behaviour  4 ethics issues in BTMA: personal privacy, data/info accuracy, intellectual property ownership, access to info  Ethical dilemmas when companies try to use IS to exploit comp. advantage. More ethics: employee surveillance, cookies (message given to web browser by web server) & super-cookie. Courts: “customers  right to privacy while searching the Internet”  Information ethics = “associated with development + application of IT”. Richard Mason – IT PAPA (privacy, accuracy, property, accessibility)  Manage privacy through choice (desired level of access), consent (grant), and control (corrections/updates)  Security & controls: protect organizational data from hackers/viruses. External threats (hackers, spam, telecommunications/server failure, DDoS) & internal threats (employee sabotage, unintentional errors, hardware/software failure, natural disasters)  Slide 22-23  Managers: control PAPA principles, limit access to customer info (respect privacy), COBIT, ITIL, decoupling  PC Era  Web 1.0  Web 2.0 (loose collection of IT + applications, plus websites)  Web 3.0 (8B+ users)  7 SM benefits: newsfeed, “alumni” networks, “like”, connectivity, building trust, marketing, gaming $$$  Personal Information Protection & Electronic Documents Act. 10 principles: accountability, identify purpose, consent, collection, use + disclosure + retention, accuracy, safeguard, openness, individual access, challenging compliance  Kevin Mitnick (world's most wanted hacker) and Wickr (secure x8994987)  3 types of safeguards involved with security: human, data, technology  IS security threats due to: software/hardware security vulnerabilities, negligence, access permission granting, malicious code, & deceitful communication  Social re-engineering = Tricking people into revealing their passwords by pretending to be legitimate users or members of a company in need of information  Authentication methods: passwords, smart cards, biometrics, sign-on, VPNs or special servers, wired networks  Public key encryption: one private key + one public key  related (data encrypted with one key can be decrypted using only the other key. Message integrity: can be certain the sent message arrives at destination without being copied/changed  4 main data safeguards: data rights & responsibilities, encryption, backup & recovery, physical security Week 9, Part 2 – Innovation Technology: Big Data, Data Mining, Analytics, Machine Learning, AI, IoT, and Blockchain  AI = machine/deep learning, neural networks, cognitive computing, recognize image/speech, natural language processing; big data analytics  IoT = big data + speed + connectivity; ↑prevalence in next 12 months.  Blockchain = secure way of leveraging nearly instantaneous transaction data; will provide a prototype for security measures to fortify IoT  Leveraging data mining analytics  IoT, AI, machine learning, block chain  COMPETITIVE ADVANTAGE  Canada ↑prominent w/technology. Sweden, UK, Switzerland = much more (culture of innovation)  Simon Sinek – “Golden Circle” – what (outer, easy to answer), how, why (philosophy, KEY)  3 processes that help innovate: innovative strategy  concept generation  business prototype ($ + explain)  Innovation culture! How? Connections, ownership (encourage ↑ideas), confidence, mgmt. example  Sustaining innovations: moving along established improvement trajectories. Disruptive innovations: new value proposition, new or reshaped existing markets.  Clayton Christensen & Innovator’s dilemma o Steady improvements in Tech = ↑ Product Performance but ↑ expectations o T1 = good, T2 = much better (improved), T3 = great (continued)! But T2 = DISRUPTIVE INNOVATOR. For original supplier: T2 (no perceived threat)  T3 (stuck on old tech)  T3 (too late to change)  market share drops while innovator’s market share soars!  Disruptive innovators = less demanding customers  sustaining for long term success. Aim to disrupt competitors, not customers, because ↑ success if ↓need for re-order  Process = Big data (volume/velocity/veracity/variety): data generated (structured/ unstructured) + stored (databases/servers). AI: data processing (algorithms, detect patterns) + actionable insights  Supervised (know what we’re predicting – train the model to generate predictions) vs. unsupervised learning (don’t know what we’re predicting – trying to put info together)  AI: building human-inspired intelligent agents that can accumulate & use big data to learn + make intelligent decisions. Ex: self-driving car  IoT  SMARTER. Data mining  algorithm  optimization  Predictive analytics: big data  info  patterns/predictions; helps to figure out customer demand + reactions  Blockchain: data store ($$ transactions, peer-to-peer networks, ≈real-time, unalterable, permissions, authorizing, cut out middle man, ↑↑↑accuracy). Analogy: blocks in a chain = pages in a book (data + meta-data)  4 blockchain principle
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